Finger Print Attendance System

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Finger Print Attendance System
Charles C. Borres
Alfe Anido H. Almonte
Engr. Maridee B. Adiong
INTRODUCTION
Authentication plays a very critical role in Attendance-related applications like e-
commerce. There are a number of methods and techniques for accomplishing this key
process. In this regard, biometrics is gaining increasing attention these days.
Attendance systems, having realized the value of biometrics, use biometrics for two
basic purposes: to verify or identify users. There is a number of biometrics and different
applications need different biometrics. Biometric is the most secure and convenient
authentication tool. It can not be borrowed, stolen, or forgotten and forging one is
practically impossible.
Biometrics measure individual's unique physical or behavioral characteristics to
recognize or authenticate their identity. Common physical biometrics includes
fingerprints, hand or palm geometry, retina, iris, and facial characteristics. Behavioral
characters characteristics include signature, voice, keystroke pattern, and gait. Project
deals with Identification, Authentication and Setup of Attendance System using SM 630
Biometrics and 8051 Microcontroller. Beside Biometrics and 8051 Microcontroller the
major components required are LCD, General purpose PCB, PC interface. The
interfacing between 8051-LCD and 8051 - SM 630 Biometrics Module (Thumb
Geometry recognition) is to be implemented. The details about each module are given in
next sections of this report.
BLOCK DIAGRAM

Figure 1.1 Block diagram of the system

THE 8051 MICROCONTROLLER

The 8051 family, 8051 assembly language programming, loop and I/O port
programming, 8051 addressing modes, arithmetic instructions, 8051 hardware
connection and Intel hex file have been discussed.
THE 8051 FAMILY
In 1981, Intel Corporation introduced an 8-bit microcontroller called the 8051. This
microcontroller had 128 bytes of RAM, 4K bytes of on-chip ROM, two timers, one serial
port, and four ports (each 8-bits wide) all on a single chip. The 8051 is an 8-bit
processor, meaning that the CPU can work on only 8 bits of data at a time. Data larger
than 8 bits has to broken into 8-bit pieces to be processed by the CPU. The 8051 has a
total of four I/O ports, each 8 bits wide. Although the 8051 can have a maximum of
64K bytes of on-chip ROM, many manufacturers have put only 4K bytes on the chip.
There are different flavors of the 8051 in terms of speed and amount of on-chip ROM,
but they are all compatible with the original 8051 as far as the instructions are
concerned. The various members of the 8051 family are 8051 microcontroller, 8052
microcontroller and 8031 microcontroller.
Block Diagram:

Figure 1.2 Block diagram of inside the microcontroller 8051
8051 Microcontroller
The 8051 is the original member of the 8051 family. Figure 2.1 shows the block
diagram of the 8051 microcontroller. The AT89S52 is a low-power, high-performance
CMOS 8-bit microcomputer with 4K bytes of Flash programmable and erasable read
only memory (PEROM). The device is manufactured using Atmel’s high-density
nonvolatile memory technology and is compatible with the industry-standard MCS-51
instruction set and pin out. The on-chip Flash allows the program memory to be
reprogrammed in-system or by a conventional nonvolatile memory programmer. By
combining a versatile 8-bit CPU with Flash on a monolithic chip, the Atmel AT89S52 is
a powerful microcomputer which provides a highly-flexible and cost-effective solution to
many embedded control applications. The AT89S52 provides the following standard
features: 8Kbytes of Flash, 256 bytes of RAM, 32 I/O lines, three 16-bittimer/counters,
five vector two-level interrupt architecture, a full duplex serial port, and on-chip
oscillator and clock circuitry. In addition, the AT89S52 is designed with static logic for
operation down to zero frequency and supports two software selectable power saving
modes. The Idle Mode stops the CPU while allowing the RAM, timer/counters, serial
port and interrupt system to continue functioning. The Power-down Mode saves the
RAM contents but freezes the oscillator disabling all other chip functions until the next
hardware reset.
Pin Description
VCC
Supply voltage.
GND
Ground.
Port 0
Port 0 is an 8-bit open-drain bi-directional I/O port. As an output port, each pin can
sink eight TTL inputs. When 1s are written to port 0 pins, the pins can be used as high-
impedance inputs. Port 0 may also be configured to be the multiplexed low- order
address/data bus during accesses to external program and data memory. In this mode
P0 has internal pull-ups. Port 0 also receives the code bytes during Flash programming,
and outputs the code bytes during program verification. External pull-ups are required
during program verification.

Figure 2.2 Pin diagram for microcontroller 8051
Port 1
Port 1 is an 8-bit bi-directional I/O port with internal pull-ups. The Port 1 output
buffers can sink/source four TTL inputs. When 1s are written to Port 1 pins they are
pulled high by the internal pull-ups and can be used as inputs. As inputs, Port 1 pins
that are externally being pulled low will source current (IIL) because of the internal pull-
ups. Port 1 also receives the low-order address bytes during Flash programming and
verification.
Port 2
Port 2 is an 8-bit bi-directional I/O port with internal pull-ups. The Port 2 output
buffers can sink/source four TTL inputs. When 1s are written to Port 2 pins they are
pulled high by the internal pull-ups and can be used as inputs. As inputs, Port 2 pins
that are externally being pulled low will source current (IIL) because of the internal pull-
ups. Port 2 emits the high-order address byte during fetches from external program
memory and during accesses to external data memory that uses 16-bit addresses
(MOVX @DPTR). In this application, it uses strong internal pull-ups when emitting 1s.
During accesses to external data memory that uses 8-bit addresses (MOVX @ RI), Port 2
emits the contents of the P2 Special Function Register. Port 2 also receives the high-
order address bits and some control signals during Flash programming and verification.

Port 3
Port 3 is an 8-bit bi-directional I/O port with internal pull-ups. The Port 3 output buffer
scan sink/source four TTL inputs. When 1s are written to Port 3 pins they are pulled
high by the internal pull-ups and can be used as inputs. As inputs, Port 3 pins that are
externally being pulled low will source current (IIL) because of the pull-ups. Port 3 also
serves the functions of various special features of the AT89S52 as listed below:
Table 2.1 Function of port 3

Port 3 also receives some control signals for Flash programming and verification.
RST
Reset input. A high on this pin for two machine cycles while the oscillator is running
resets the device.
ALE/PROG
Address Latch Enable output pulse for latching the low byte of the address during
accesses to external memory. This pin is also the program pulse input (PROG) during
Flash programming. In normal operation ALE is emitted at a constant rate of 1/6 the
oscillator frequency, and may be used for external timing or clocking purposes. Note,
however, that one ALE pulse is skipped during each access to external Data Memory. If
desired, ALE operation can be disabled by setting bit 0 of SFR location 8EH. With the
bit set, ALE is active only during a MOVX or MOVC instruction. Otherwise, the pin is
weakly pulled high. Setting the ALE-disable bit has no effect if the microcontroller is in
external execution mode.
PSEN
Program Store Enable is the read strobe to external program memory. When the
AT89S52 is executing code from external program memory, PSEN is activated twice
each machine cycle, except that two PSEN activations are skipped during each access
to external data memory.
EA/VPP
External Access Enable. EA must be strapped to GND in order to enable the device
to fetch code from external program memory locations starting at 0000H up to FFFFH.
Note, however, that if lock bit 1 is programmed, EA will be internally latched on reset.
EA should be strapped to VCC for internal program executions. This pin also receives
the 12-volt programming enable voltage (VPP) during Flash programming, for parts that
require 12-volt VPP.
XTAL1
Input to the inverting oscillator amplifier and input to the internal clock operating
circuit.
XTAL2
Output from the inverting oscillator amplifier. Oscillator Characteristics XTAL1 and
XTAL2 are the input and output, respectively, of an inverting amplifier which can be
configured for use as an on-chip oscillator, as shown in Figure 1. Either a quartz crystal
or ceramic resonator may be used. To drive the device from an external clock source,
XTAL2 should be left unconnected while XTAL1 is driven as shown.

Figure 2.3 Crystal Oscillator Connections
There are no requirements on the duty cycle of the external clock signal, since the
input to the internal clocking circuitry is through a divide-by-two flip-flop, but
minimum and maximum voltage high and low time specifications must be observed.

BIOMETRICS
Humans recognize each other according to their various characteristics for ages.
We recognize others by their face when we meet them and by their voice as we speak to
them. Identity verification (authentication) in computer systems has been traditionally
based on something that (key, magnetic or chip card) or (PIN, password). Things like
keys or cards, however, tend to get stolen or lost and passwords are often forgotten or
disclosed.
To achieve more reliable verification or identification we should use something
that really characterizes the given person. Biometrics offer automated methods of
identity verification or identification on the principle of measurable physiological or
behavioral characteristics such as a fingerprint or a voice sample. The characteristics
are measurable and unique. These characteristics should not be duplicable, but it is
unfortunately often possible to create a copy that is accepted by the biometric system
as a true sample. This is a typical situation where the level of Attendance provided is
given as the amount of money the impostor needs to gain an unauthorized access. We
have seen biometric systems where the estimated amount required is as low as $100 as
well as systems where at least a few thousand dollars are necessary.
Biometric systems can be used in two different modes. Identity occurs when the
user claims to be already enrolled in the system (presents an ID card or login name); in
this case the biometric data obtained from the user is compared to the user’s data
already stored in the database. Identification occurs when the identity of the user is a
priori unknown. In this case the user’s biometric data is matched against all the
records in the database as the user can be anywhere in the database or he/she actually
does not have to be there at all.
It is evident that identification is technically more challenging and costly.
Identification accuracy generally decreases as the size of the database grows. For this
reason records in large databases are categorized according to a sufficiently
discriminating characteristic in the biometric data. Subsequent searches for a
particular record are searched within a small subset only. This lowers the number of
relevant records per search and increases the accuracy (if the discriminating
characteristic was properly chosen).
Before the user can be successfully verified or identified by the system, he/she
must be registered with the biometric system. User’s biometric data is captured,
processed and stored. As the quality of this stored biometric data is crucial for further
authentications, there are often several (usually 3 or 5) biometric samples used to
create user’s master template. The process of the user’s registration with the biometric
system is called enrollment.
What to measure?
Most significant difference between biometric and traditional technologies lies in
the answer of the biometric system to an authentication/identification request.
Biometric systems do not give simple yes/no answers. While the password either is
’abcd’ or not and the card PIN 1234 either is valid or not, no biometric system can verify
the identity or identify a person absolutely. The person’s signature never is absolutely
identical and the position of the finger on the fingerprint reader will vary as well.
Instead, we are told how similar the current biometric data is to the record stored in the
database. Thus the biometric system actually says what is the probability of these two
biometric samples come from the same person.
Biometric technologies can be divided into 2 major categories according to what
they measure:
1. Devices based on physiological characteristics of a person (such as the
fingerprint or hand geometry).
2. Systems based on behavioral characteristics of a person (such as signature
dynamics).
Biometric systems from the first category are usually more reliable and accurate
as the physiological characteristics are easier to repeat and often are not affected by
current (mental) conditions such as stress or illness. One could build a system that
requires a 100%match each time. Yet such a system would be practically useless, as
only very few users (if any) could use it. Most of the users would be rejected all the time,
because the measurement results never are the same. We have to allow for some
variability of the biometric data in order not to reject many authorized users.
However, the greater variability we allow the greater is the probability that an
impostor with a similar biometric data will be accepted as an authorized user. The
variability is usually called a (Attendance) threshold or a (Attendance) level. If the
variability allowed is small then the Attendance threshold or the Attendance level is
called high and if we allow for greater variability then the Attendance threshold or the
Attendance level is called low.
Biometric Techniques
There are lots of biometric techniques available nowadays. A few of them are in
the stage of the research only (e.g. the odor analysis), but a significant number of
technologies is already mature and commercially available (at least ten different types of
biometrics are commercially available nowadays: fingerprint, finger geometry, hand
geometry, palm print, iris pattern, retina pattern, facial recognition, voice comparison,
signature dynamics and typing rhythm).
Fingerprint technologies
Fingerprint identification is perhaps the oldest of all the biometric techniques.
Fingerprints were used already in the Old China as a means of positively identifying a
person as an author of the document. Their use in law enforcement since the last
century is well known and actually let to an association fingerprint = crime. This caused
some worries about the user acceptance of fingerprint-based systems. The situation
improves as these systems spread around and become more common. Fingerprint
readers before we can proceed any further we need to obtain the digitalized fingerprint.
The traditional method uses the ink to get the fingerprint onto a piece of paper. This
piece of paper is then scanned using a traditional scanner. This method is used only
rarely today when an old paper-based database is being digitalized, scanning a
fingerprint found on a scene of a crime is being processed or in law enforcement AFIS
systems. Otherwise modern live fingerprint readers are used. They do not require the
ink anymore. These live fingerprint readers are most commonly based on optical,
thermal, silicon or ultrasonic principles.



Figure 3.1 Optical Scanner
All the optical fingerprint readers comprise of the Source of light, the light sensor
and a special reflection surface that changes the reflection according to the pressure.
Some of the readers are fitted out with the processing and memory chips as well.
Optical finger print readers are the most common at present. They are based on
reflection changes at the spots where the finger papillary lines touch the reader’s
surface. The size of the optical fingerprint readers typically is around 10 x 10 x 5
centimeters. It is difficult to minimize them much more as the reader has to comprise
the source of light, reflection surface and the light sensor. The optical fingerprint
readers work usually reliably, but sometimes have problems with dust if heavily used
and not cleaned. The dust may cause latent fingerprints, which may be accepted by the
reader as a real fingerprint. Optical fingerprint readers cannot be fooled by a simple
picture of a fingerprint, but any 3D fingerprint model makes a significant problem, all
the reader checks is the pressure. A few readers are therefore equipped with additional
detectors of finger aliveness.




Figure 3.2 Fingerprint bitmap
Optical readers are relatively cheap and are manufactured by a great number of
manufacturers. The field of optical technologies attracts many newly established firms
(e.g., American Biometric Company, Digital Persona) as well as a few big and well -
known companies (such as HP, Philips or Sony). Optical fingerprint readers are also
often embedded in keyboards, mice or monitors.



Figure 3.3 Optical fingerprint reader
Silicon technologies are older than the optical technologies. They are based on the
capacitance of the finger. The dc-capacitive silicon fingerprint sensors consist of
rectangular arrays of capacitors on a silicon chip. One plate of the capacitor is the
finger; the other plate is a tiny area of metallization (a pixel) on the chip’s surface. One
places his/her finger against the surface of the chip (actually against an insulated
coating on the chip’s surface). The ridges of the fingerprint are close to the nearby pixels
and have high capacitance to them. The valleys are more distant from the pixels nearest
them and therefore have lower capacitance.
Such an array of capacitors can be placed onto a chip as small as 15 x 15 x 5 mm
and thus is ideal for miniaturization. A PCMCIA card (the triple height of a credit card)
with a silicon fingerprint reader is already available. Integration of a fingerprint reader
on a credit card-sized smartcard was not achieved yet, but it is expected in the near
future. Silicon fingerprint readers are popular also in mobile phones and laptop
computers due to the small size. The fingerprint bitmap obtained from the silicon reader
is affected by the finger moisture as the moisture significant influences the capacitance.
This often means that too wet or dry finger do not produce bitmaps with a sufficient
quality and so people with unusually wet or dry finger do not produce bitmaps with a
sufficient quality and so people with unusually wet or dry finger have problems with
these silicon fingerprint readers.
Both optical and silicon fingerprint readers are fast enough to capture and display
the fingerprint in real time. The typical resolution is around 500 DPI.Ultrasonic
fingerprint readers are the newest and least common. They use ultrasound to monitor
the finger surface.
The user places the finger on a piece of glass and the ultrasonic sensor moves and
reads whole the fingerprint. This process takes one or two seconds. Ultrasound is not
disturbed by the dirt on the finger so the quality of the bitmap obtained is usually fair.
Ultrasonic fingerprint readers are manufactured by a single company nowadays. This
company (Ultra Scan Inc.) owns multiple patents for the ultrasonic technology. The
readers produced by this company are relatively big (15 x15 x 20 centimeters), heavy,
noisy and expensive (with the price around $2500). They are able to scan fingerprint at
300, 600 and 1000 DPI (according to the model).
Fingerprint processing Fingerprints are not compared and usually also not stored
as bitmaps. Fingerprint matching techniques can be placed into two categories:
minutiae-based and correlation based. Minutiae-based techniques find the minutiae
points’ first and then map their relative placement on the finger. Minutiae are individual
unique character- minutiae istics within the fingerprint pattern such as ridge endings,
bifurcations, divergences, dots or islands (see the picture on the following page). In the
recent years automated fingerprint comparisons have been most often based on
minutiae.
The problem with minutiae is that it is difficult to extract the minutiae points
accurately when the fingerprint is of low quality. This method also does not take into
account the global pattern of ridges and furrows. The correlation-based method is able
to correlation based overcome some of the difficulties of the minutiae-based approach.
However, it has some of its own shortcomings. Correlation-based techniques require the
precise location of a registration point and are affected by image translation and
rotation.



Loop Arch Whorl
Figure 3.4 Loop, Arch& Whorl
The loop is the most common type of fingerprint pattern and accounts for about
65% of all prints. The arch pattern is a more open curve than the loop. There are two
types of arch patterns: the plain arch and the tented arch. Whorl patterns occur in
about 30% of all fingerprint and are defined by at least one ridge that makes a complete
circle.
The readability of a fingerprint depends on a variety of work and environmental
factors. These include age, gender, occupation and race. A young, female, Asian mine-
worker is seen as the most difficult subject. A surprisingly high proportion of the
populations have missing finger, with the left forefinger having the highest percentage
at 0.62%. There are about 30 minutiae within a typical fingerprint image obtained by a
live fingerprint reader. The number and spatial distribution of minutiae varies according
to the quality of the fingerprint image, finger pressure, moisture and placement. In the
decision process, the biometric system tries to find minutiae transformation between
the current distribution and the stored template. The matching decision is then based
on the possibility and complexity of the necessary transformation. The decision usually
takes from 5 milliseconds to 2 seconds.







Figure 3.5 Fingerprint ridge
These are not continuous, straight ridges. Instead they are broken, forked,
changed directionally, or interrupted. The points at which ridges end, fork and change
are called minutia points and these minutia points provide unique, identifying
information. There area number of types of minutia points. The most common are ridge
endings and ridge bifurcations (points at which a ridge divides into two or more
branches).
The speed of the decision sometimes depends on the Attendance level and the
negative answer very often takes longer time than the positive one (sometimes even 10
times more). There is no direct dependency between the speed and accuracy of the
matching algorithm according to our experience. We have seen fast and accurate as well
as slow and less accurate matching algorithms.
The minutiae found in the fingerprint image are also used to store the fingerprint
for future comparisons. The minutiae are en- templates coded and often also
compressed. The size of such a master template usually is between 24 bytes and one
kilobyte.



Figure 3.6 The minutiae matching
The minutia matching is a process where two sets of minutiae are compared to
decide whether they represent the same finger or not.
Fingerprints contain a large amount of data. Because of the high level of data
present in the image, it is possible to eliminate false matches and reduce the number of
possible matches to a small fraction. This means that the fingerprint technology can be
used for identification even within large databases. Fingerprint identification technology
has undergone an extensive research and development since the seventies. The initial
reason for the effort was the response to the FBI requirement for an identification
search system. Such systems are called Automated Fingerprint Identification Systems
(AFIS) and are used to identify individuals in large AFIS databases (typically to find the
offender of a crime according to a fingerprint found at the crime scene or to identify a
person whose identity is unknown). AFIS systems are operated by professionals who
manually intervene the minutiae extraction and matching process and thus their
results are really excellent. The typical access control systems, on the other side, are
completely automated. Their accuracy is slightly worse. The quality of the fingerprint
image obtained by an automated fingerprint reader from an inexperienced (non-
professional) user is usually lower. Access control systems Fingerprint readers often do
not show any fingerprint preview and so the users do not know if the positioning and
pressure of the finger is correct. The automatic minutiae extraction in a lower quality
image is not perfect yet. Thus the overall accuracy of such a system is lower.
Some newer systems are based not only on minutiae extraction; they use the
length and position of the papillary lines as well. A few system take into account even
pores (their spatial distribution), pores but the problem with pores is that they are too
dependent on the fingerprint image quality and finger pressure. Most of the biometric
fingerprint systems use the fingerprint reader to provide for the fingerprint bitmap
image only, whole the processing and matching is done by a software that runs on a
computer (the software is often available for Microsoft Windows operating systems only).
There are currently only very few fingerprint devices that does all the processing by the
hardware.
The manufacturers of the fingerprint readers used to deliver the fingerprint
processing software with the hardware. Today, the market specializes. Even if it is still
possible to buy a fingerprint reader with a software package (this is the popular way
especial for the low-end devices for home or office use) there are many manufacturers
that produce fingerprint hardware only (e.g. fingerprint silicon chips by Thomson) or
software companies that offer device-independent fingerprint processing software.
Device independent software is not bound to images obtained by one single input
device, but their accuracy is very low if various input devices are mixed.
The Layer model
Although the use of each biometric technology has its own specific issues, the
basic operation of any biometric system is very similar. The system typically follows the
same set of steps. The typical steps separation of actions can lead to identifying critical
issues and to improving Attendance of the overall process of biometric authentication.
The whole process starts with the enrollment:
First measurement (acquisition)
This is the first contact of the user with the biometric system. The user’s biometric
sample is obtained using an input device. The quality of the first biometric sample is
crucial for further authentications of the user, so the quality of this biometric sample
must be particularly checked and if the quality is not sufficient, the acquisition of the
biometric sample must be repeated. It may happen that even multiple acquisitions do
not generate biometric samples with quality is crucial sufficient quality. Such a user
cannot be registered with the system. There are also mute people, people without finger
or with injured eyes. Both these categories create a “failed to enroll “group of users.
Users very often do not have any previous experiences with the kind of the biometric
system they are being registered with, so their behavior at the time of the first contact
with the technology is not natural. This negatively influences the quality of the first
measurement and that is why the first measurement is guided by a professional who
explains the use of the biometric reader.
Creation of master characteristics the biometric measurements are processed after
the acquisition. The number of biometric samples necessary for further processing is
based on the nature of the used biometric technology. Sometimes a single sample is
sufficient, but often multiple biometric samples are required. The biometric
characteristics are most commonly neither compared nor stored in the raw format (say
as a bitmap). The raw measurements contain a lot of noise or irrelevant information,
which need not be stored. So the measurements are processed and only the important
features are extracted and used. This significant reduces the size of the data. The
process of feature extraction is not lossless and so the extracted features cannot be
used to reconstruct the biometric sample completely.
Storage of master characteristics after processing the first biometric sample and
extracting the features, we have to store (and maintain) the newly obtained master
template. Choosing a proper discriminating characteristic for the categorization of
records in large databases can improve identification (search) tasks later on. There are
basically 4 possibilities where to store the template: in a card, in the central database
on a server, on a workstation or directly in an authentication terminal. The storage in
an authentication terminal cannot be used for template must be encrypted large-scale
systems, in such a case only the first two possibilities are applicable. If privacy issues
need to be considered then the storage on a card has an advantage, because in this
case no biometric data must be stored (and potentially misused) in a central database.
The storage on a card requires a kind of a digital signature of the master template and
of the association of the user with the master template. Biometric samples as well as
the extracted features are very sensitive data and so the master template should be
stored always encrypted no matter what storage is used.
As soon as the user is enrolled, he/she can use the system for successful
authentications or identification. This process is typically fully automated and takes the
following steps:
Acquisition(s) The current biometric measurements must be obtained for the
system to be able to make the comparison with the master template. These subsequent
acquisitions of the user’s biometric measurements are done at various places where the
authentication of the user is required. This might be user’s computer in the office, an
ATM machine or a sensor in front of a door. For the best performance the kind of the
input device used at the enrollment and for the subsequent acquisitions should be the
same. Other conditions of use should also be as similar as possible with the conditions
at the enrollment. These include the background (face recognition), the background
noise (voice verification) or the moisture (fingerprint). While the enrollment is usually
guided by trained personnel, the subsequent biometric measurements are most
commonly fully automatic and unattended. This brings up a few special issues. Firstly,
the user needs to know how to use the device to provide the sample in the best quality.
This is often not easy because the device does not show any preview of the sample
obtained, so for example in the case of a fingerprint reader, the user does not know
whether the positioning of the finger on the reader and the pressure is correct.
Secondly, as the reader is left unattended, it is up to the reader to check that the
measurements obtained really belong to live persons (the aliveness property). For
example, a fingerprint reader aliveness test should tell if the fingerprint it gets is from a
live finger, not from a mask that is put on top of a finger. Similarly, an iris scanner
should make sure that the iris image it is getting is from a real eye not a picture of an
eye. In many biometric techniques (e.g. fingerprinting) the further processing trusts the
biometric hardware to check the aliveness of the person and provide genuine biometric
measurements only. Some other systems (like the face recognition) check the user’s
aliveness in software (the proper change of a characteristic with time). No matter
whether hardware or software is used, ensuring that the biometric measurements are
genuine is crucial for the system to be secure. Without the assumption of the genuine
data obtained at the input we cannot get a secure system. It is not possible to formally
prove that a reader provides only genuine measurements and this affects also the
possibility of a formal proof attacks and of the Attendance of whole the biometric
system. The aliveness test of a person is not an easy task. New countermeasures are
always to be followed by newer attacks. We do not even know how efficient the current
countermeasures are against the attacks to come. Biometric readers are not yet the
main target of sophisticated criminals. But then we can expect a wave of professional
attacks. We have seen a few biometric readers where the estimated cost of an attack is
as low as a few hundred dollars. The Attendance of such a system is really poor
Creation of new characteristics the biometric measurements obtained in the previous
step is processed and new characteristics are created. The process of feature extraction
is basically the same as in the case of the enrollment. Only a single biometric sample is
usually available. This might mean that the number or quality of the features extracted
is lower than at the time of enrollment.
Comparison the currently computed characteristics are then compared with the
characteristics obtained during enrollment. This process is very dependent on the
nature of the biometric technology used. Sometimes the desired Attendance threshold is
a parameter of the matching process, sometimes the biometric system returns a score
within range. If the system performs verification then the newly obtained characteristics
are compared only with one master template (or with a small number of master
templates, e.g. a set of master templates for a few different finger). For an identification
request the new characteristics are matched against a large number of master
templates (either against all the records in the database or if the database is clustered
then against the relevant part of the database.




SM630
SM630 background highlight optical fingerprint verification module is the latest
release of Miaxis Biometrics Co., Ltd. It consists of optical fingerprint sensor, high
performance DSP processor and Flash. It boasts of functions such as fingerprint Login,
fingerprint deletion, fingerprint verification, fingerprint upload, fingerprint download,
etc. Compared to products of similar nature, SM630 enjoys the following unique
Features:
● Self-proprietary Intellectual Property
Optical fingerprint collection device, module hardware and fingerprint algorithm are all
self developed by Miaxis.
● High Adaptation to Fingerprints
When reading fingerprint images, it has self-adaptive parameter adjustment
mechanism, which improves imaging quality for both dry and wet fingers. It can be
applied to wider public.
● Algorithm with Excellent Performance
SM630 module algorithm is specially designed according to the image generation theory
of the optical fingerprint collection device. It has excellent correction & tolerance to
deformed and poor-quality fingerprint.
● Easy to Use and Expand
User does not have to have professional know-how in fingerprint verification. User can
easily develop powerful fingerprint verification application systems based on the rich
collection of controlling command provided by SM630 module. All the commands are
simple, practical and easy for development.
● Low Power Consumption
Operation current <80mA, specially good for battery power occasions.






Basic Feature
Hardware Specification
Table 3.1 Hardware specification of SM630
Fingerprint enrollment time 250ms
Fingerprint search time <1s 100 fingerprint, average value in
test
Resolutions 500DPI
Capacity 256 templates
FAR 0.0001%
FRR 0.01%
Supply power 4.3V 6V
Working current <80mA
Peak current <90mA
Communication interface TTL
Communication Baud rate 57600bps
Working temperature
-10℃ +40℃
Working humidity 40 RH 85 RH no dew
Module dimension 60.0×21×25mm L*W*H
External Port
1. External Interface Connection (JP1)

Table 3.3 Pin description of SM 630


SERIAL COMMUNICATION
Basics:

Computer transfers data in two ways these are
1. Parallel: Often 8 or more lines (wire conductors) are used to transfer data to a
device that is only few feet away.
2. Serial: To transfer to a device located many meters away, the serial method is
used. The data is sent one bit at a time.

Figure 4.1 Mode of Communication
At the transmitting end, the byte of data must be converted to serial bits using
parallel-in-serial-out shift register. At the receiving end, there is a serial-in-parallel-out
shift register to receive the serial data and pack them into byte. When the distance is
short, the digital signal can be transferred as it is on a simple wire and requires no
modulation. If data is to be transferred on the telephone line, it must be converted from
0s and 1s to audio tones. This conversion is performed by a device called a modem,
“Modulator/demodulator”.
Serial data communication uses two methods. First are synchronous method
transfers a block of data at a time. Second is an asynchronous method transfer a single
byte at a time.
It is possible to write software to use either of these methods, but the programs can
be tedious and long. There are special IC chips made by many manufacturers for serial
communications namely UART (universal asynchronous Receiver-transmitter) & USART
(universal synchronous-asynchronous Receiver-transmitter).

Figure 4.2 Diagrammatic Simplex & Duplex Transmission
A protocol is a set of rules agreed by both the sender and receiver. Asynchronous
serial data communication is widely used for character-oriented transmissions where
each character is placed in between start and stop bits, this is called framing and
block-oriented data transfers use the synchronous method. The start bit is always one
bit, but the stop bit can be one or two bits the start bit is always a 0 (low) and the stop
bit(s) is 1 (high).

Figure 4.3 Transmissions of Data
Due to the extended ASCII characters, 8-bit ASCII data is common in modern PCs
the use of one stop bit is standard. Assuming that we are transferring a text file of
ASCII characters using 1 stop bit, we have a total of 10 bits for each character. In some
systems in order to maintain data integrity, the parity bit of the character byte is
included in the data frame. The rate of data transfer in serial data communication is
stated in bps (bits per second).
Another widely used terminology for bps is baud rate. As far as the conductor wire is
concerned, the baud rate and bps are the same, and we use the terms interchangeably.
The data transfer rate of given computer system depends on communication ports
incorporated into that system.
An interfacing standard RS232 was set by the Electronics Industries Association
(EIA) in 1960. The standard was set long before the advent of the TTL logic family, its
input and output voltage levels is not TTL compatible where a 1 is represented by -3 ~ -
25 V, while a 0 bit is +3 ~ +25 V, making -3 to +3 undefined.
MAX232
A line driver required to convert RS232 voltage levels to TTL levels, and vice versa. It
includes a capacitive voltage generator to supply TIA/EIA-232-F voltage levels from a
single 5-V supply. Each receiver converts TIA/EIA-232-F inputs to 5-V TTL/CMOS
levels. These receivers have a typical threshold of 1.3 V, a typical hysteresis of 0.5 V,
and can accept ±30-V inputs. Each driver converts TTL/CMOS input levels into
TIA/EIA-232-F levels.
Pin Diagram

Figure 4.4 MAX 232 pin configuration
Connection with Microcontroller and DB9:

Figure 4.5 Connections with Microcontroller and DB9
8051 has two pins that are used specifically for transferring and receiving data
serially. These two pins are called TxD and RxD and are part of the port 3 group (P3.0
and P3.1).These pins are TTL compatible; therefore, they require a line driver to make
them RS232 compatible. To allow data transfer between the PC and an 8051 system
without any error, we must make sure that the baud rate of 8051 system matches the
baud rate of the PC’s COM port.
REGISTER STRUCTURE
SBUF Register: This is an 8-bit register used solely for serial communication. For a
byte data to be transferred via the TxD line, it must be placed in the SBUF register. The
moment a byte is written into SBUF, it is framed with the start and stop bits and
transferred serially via the TxD line. SBUF holds the byte of data when it is received by
8051 RxD line. When the bits are received serially via RxD, the 8051 defames it by
eliminating the stop and start bits, making a byte out of the data received, and then
placing it in SBUF.
SCON Register: SCON is an 8-bit register used to program the start bit, stop bit, and
data bits of data framing, among other things.
Table 4.1 Functions of various bits in SCON register

SM0, SM1: They determine the framing of data by specifying the number of bits per
character, and the start and stop bits.
Table 4.2 Mode selection using SM0 & SM1


SM2: This enables the multiprocessing capability of the 8051.
REN (receive enable): It is a bit-addressable register. When it is high, it allows 8051 to
receive data on RxD pin. If low, the receiver is disables (transmit interrupt). When 8051
finishes the transfer of 8-bit character. It raises TI flag to indicate that it is ready to
transfer another byte. TI bit is raised at the beginning of the stop bit RI (receive
interrupt). When 8051 receives data serially via RxD, it gets rid of the start and stop
bits and places the byte in SBUF register. It raises the RI flag bit to indicate that a byte
has been received and should be picked up before it is lost. RI is raised halfway through
the stop bit.
LCD Unit
A liquid crystal display (LCD) is a thin, flat display device made up of any number of
color or monochrome pixels arrayed in front of a light source or reflector. It is prized by
engineers because it uses very small amounts of electric power, and is therefore
suitable for use in battery-powered electronic devices.
Each pixel consists of a column of liquid crystal molecules suspended between two
transparent electrodes, and two polarizing filters, the axes of polarity of which are
perpendicular to each other. Without the liquid crystals between them, light passing
through one would be blocked by the other. The liquid crystal twists the polarization of
light entering one filter to allow it to pass through the other.
The molecules of the liquid crystal have electric charges on them. By applying small
electrical charges to transparent electrodes over each pixel or sub pixel, the molecules
are twisted by electrostatic forces. This changes the twist of the light passing through
the molecules, and allows varying degrees of light to pass (or not to pass) through the
polarizing filters. Before applying an electrical charge, the liquid crystal molecules are in
a relaxed state. Charges on the molecules cause these molecules to align themselves in
a helical structure, or twist (the "crystal").
When an electrical charge is applied to the electrodes, the molecules of the liquid
crystal align themselves parallel to the electric field, thus limiting the rotation of
entering light. If the liquid crystals are completely untwisted, light passing through
them will be polarized perpendicular to the second filter, and thus be completely
blocked. The pixel will appear unlit. By controlling the twist of the liquid crystals in
each pixel, light can be allowed to pass though in varying amounts, correspondingly
illuminating the pixel.

Figure 4.10 LCD Display
Pin description of LCD

Table 4.3 Pin description of LCD

Schematic for system PCB connections



PIN SYMBOL
I/O
DESCRIPTIONS
1 VSS ------
--
GROUND
2 VCC ------
--
+5V POWER SUPPLY
3 VEE -------
--
POWER SUPPLY TO CONTROL CONTRAST
4 RS I RS=O TO SELECT COMMAND REGISTER
RS=1 TO SELECT DATA REGISTER
5 R/W I R/W=0 FOR WRITE,R/W=1 FOR READ
6 E I/O ENABLE
8TO 14 DB0 TO DB14 I/O 8 BIT DATA BUSES
Block diagram

Figure 5.1 Block diagram of the authentication process
How to operate the Hardware
1. Connect the hardware to the PC serial port
2. Switch on the power supply.
3. Open the software with the password “nokia”
4. Select the serial port number on the PC software and click Open
5. You can now ADD/Delete the finger prints from the PC.
6. After ADDing the fingerprint, create a New record with the ID shown on the LCD.
7. You can add records on clicking the “View Records” button
8. You can generate reports by clicking the “View Attendance Records”

Figure 5.2: Screenshot of Attendance System

Figure 5.3: Attendance Sheet

Result and Conclusion

The project report began with the introduction to the basic functioning of
Microcontroller based Identification, Authentication and Setup of Attendance system.
Project deals with Microcontroller as central controlling units for various other sections
like Biometrics SM 630 module, LCD, PC interface, IR sensor section etc. Interfacing
between all sections required for system and microcontroller AT89S52 has been done
successfully. For registration press the add button to store the finger print into the
biometrics module. When a new person who is not register with the system try to have
access, system refuses access and displays message “Fingerprint NOT Matched”. For
the person who is registered with the system will updated with his name on the
database for attendance.
There are many mature biometric systems are available now. Proper design and
implementation of the biometric system can indeed increase the overall Attendance;
especially the smartcard based solutions seem to be very promising. Making a secure
biometric systems is, however, not as easy as it might appear. The word biometrics is
very often used as a synonym for the perfect Attendance. This is a misleading view.
There are numerous conditions that must be taken in account when designing a secure
biometric system. First, it is necessary to realize that biometrics is not secrets. This
implies be careful that biometric measurements cannot be used as capability tokens
and it is not secure to generate any cryptographic keys from them. Second, it is
necessary to trust the input device and make the communication link secure. Third, the
input device needs to check the live ness of the person being measured and the device
itself should be verified for example by a challenge-response protocol.

Future scopes
The above developed system is quit versatile in nature. So many applications can be
added with the same system by just little modification required.
1. Attendance system module can also be interfaced with the same existing
system which keeps the record (Identity, Time, Date etc.) of that person and
corresponding data base can be maintained. IC 74LS244 can be used for
multiplexing RxD and TxD to creating the hardware for attendance system.
2. Same system can be implemented at high Attendance area, where only selected
persons are allowed.
3. The end part of the system, i.e., finger print scanner can be replaced by RF Id
scanner and ID cards containing persons ID no. (Tag) can be given to the
persons. During scanning data base related to person’s position can be
maintained. Only little changes are required in main programming with
appropriate hardware.

Bibliography:
1. Muhammad Ali Mazidi, Janice Gillispi Mazidi and Rolin D. Mckinlay, The 8051
Microcontroller and Embedded Systems: Using assembly and C 2nd Edition, Delhi:
Pearson Prentic Hall, 2006.
2. http://www.nxp.com/acrobat_download/datasheets/P89CV51RB2_RC2_RD2_2.
pdf
3. http://www.atmel.com/dyn/resources/prod_documents/doc0265.pdf
4. http://www.miaxis.net/1070015/1/12/products_details.htm?menu=1
5. http://www.8051projects.info
6. http://www.atmel.com/litrature
7. http://www.en.wikipedia.org/wiki/Fingerprint_recognition
8. http://www.keil.com/uvision/

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