Face Recognition Based Attendance System with Auto Alert to Guardian using Call and SMS

International Journal of Trend in Scientific Research and Development (IJTSRD)
Volume: 3 | Issue: 4 | May-Jun 2019 Available Online: www.ijtsrd.com e-ISSN: 2456 - 6470
@ IJTSRD | Unique Paper ID - IJTSRD23928 | Volume – 3 | Issue – 4 | May-Jun 2019 Page: 792
Face Recognition Based Attendance System with
Auto Alert to Guardian using Call and SMS
Diksha Ghare1, Prajakta Katakdhod1, Shraddha Ujgare1, Komal Suskar1, Prof. Amruta Surana2
1Student, 2Professor
1,2Department of Computer Engineering, PCET’s NMIET, Talegaon Dabhade, Maharashtra, India
How to cite this paper: Diksha Ghare |
Prajakta Katakdhod | Shraddha Ujgare |
Komal Suskar | Prof. Amruta Surana
"Face Recognition Based Attendance
System with Auto Alert to Guardian
using Call and SMS" Published in
International Journal of Trend in
Scientific Research and Development
(ijtsrd), ISSN: 2456-
6470, Volume-3 |
Issue-4, June 2019,
pp.792-795, URL:
https://www.ijtsrd.c
om/papers/ijtsrd23
928.pdf
Copyright © 2019 by author(s) and
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ABSTRACT
Now a days the wise attending management system victimization facedetection
techniques. Daily attending marking could also be a typical and vital activity in
colleges and colleges forcheckingtheperformanceof students.Manualattending
maintaining is tough methodology, significantly for large cluster of students.
Some machine-driven systems developed to x beat these difficulties, have
drawbacks like worth, faux attending, accuracy, meddlesomeness. Tobeatthese
drawbacks, there is need of good and automatic attending system. We’ve a bent
to unit implementing attending system victimization face recognition.Sinceface
is exclusive identity of person, the problem of pretend attending and proxies
could also be resolved. The system uses native binary pattern face recognition
technique because it is fast, straightforward and has larger successrate.Also,it's
pro-vision to have an effect on intensityof sunshinedrawback andhead produce
draw back that produces it effective. This wise system could also be degree
effective because of maintain the degree will-less squat recognition system is
planned supported appearance-based choicesthat concentrateon theshortened
squatter image rather than native countenance. The remainder step in squatter
recognition system is squatter detection Viola-Jones squatter detection
methodology that capable of method photos terribly whereas achieving higher
detection rates is utilized. The completesquatter recognition methodologycould
also be divided into a pair of parts squatter detection andsquatteridentification.
For face detection, Viola Jones face detection methodology has been used out of
the many face detection ways that. Once face detection, face is cropped from the
actual image to urge obviate the background.Chemistfacesand shearfacesways
that are used for face identification. Average photos of subjects area unitused as
coaching job set to spice up the accuracy of identification.
Keywords: Face Authentication, Vailo and Jones Algorithm, SMS, Auto Call
I. INTRODUCTION
The system permits simple attending management
victimization the Face Detection, that's one in each of the
foremost acceptable techniques. The teacher should carry a
Digital Image Capturing Devices to the room and take a
picture of the students. The teacher then should log-intothe
computer victimization his/her login credentials. System
together consists of information which containsphotosof all
the students and their personal details. The information
together keeps record of details of lecturers of the assorted
classes. Once the image is uploaded to the system, faces of
scholar’s are detected from the image hold on. These photos
are then compared with {the photos pictures} the
photographs} of student’s hold on images inside the
information victimization face recognition algorithmic rule
and record of attending is unbroken. In manyinstitutionand
Organization the attending is also a necessary issue to take
care of the record of lectures, pay and work hours etc. Most
of the institutes and organizations follow the manual
technique exploitation previous paper and lupus technique
and a number of them have shifted to biometric technique.
this system that schools use is that the professor passes a
sheet or build roll calls and mark the attending of the
students and this sheet a lot of goes totheadmindepartment
with updates the final surpass sheet. This method is
reasonably feverish and time intense. Also, for professorsor
employees at institutes or organizations the biometric
system serves one at a time. So, why notshifttoanautomatic
attending system that works on face recognition technique?
Be it a class space or entry gates it will mark the attending of
the students, professors, employees, etc.
II. SYSTEM OVERVIEW
This system uses Viola and Jones formula for detectivework
and recognizing the faces.
The main elements of this technology square measure as
follows:
A. Face Detection.
B. Face Recognition.
A. Face Detection: Face detection isalsoatechnologybeing
utilized throughout a sort of applications that identifies
human faces in digital footage. Face detection
collectively refers to the psychological methodology by
IJTSRD23928

International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
that humans notice and attend to faces throughout a
visible scene. Face detection is taken into account a
selected case of object-class detection. In object-class
detection, the task is to seek out the locations and sizes
of all objects in a very image that belong to a given class.
Examples embody higher torsos, pedestrians, and cars.
Face-detection algorithms focus on the detection of
frontal human faces. It’s analogous to image detection
throughout that the image of somebody is matched bit
by bit. Image matches with the image stores in
information. Any facial feature changes inside the data
will invalidate the matching methodology. A reliable
face-detection approach supported the genetic formula
and also the
B. Face Recognition: A face recognition system is also a
laptop application capable of distinctive or accessory
somebody from a digital image or a video frame from a
video offer. One amongst the ways in which to do to the
current is by scrutinyelects countenancefromtheimage
and facial information. It always utilized in security
systems and will be compared to completely different
life science like fingerprint or eye iris recognition
systems. Some face recognition algorithms verify
countenance by extracting landmarks, or options, from
an image of the themes face. For example, associate
degree formula might analyze the relative position, size,
and/or variety of the eyes, nose, cheekbones, and jaw.
These choices square measure then used to hunt for
completely different footage with matching choices.
Completely different algorithms normalize a gallery of
face footage then compress the face info, exclusively
saving the knowledge inside the image thatishelpfulfor
face recognition. An explorationimageisthen compared
with the face info. One amongst the earliest productive
systems is based on guide matching techniques applied
to a group of salient countenance, providing a variety of
compressed face illustration.
III. LITERATURE SURVEY
Paper 1:-Face RecognitionunderVaryingIlluminationUsing
Gradient faces.
Author Name: -Taiping Zhang ; Yuan Yan Tang ; Bin Fang ;
Zhaowei Shang ; Xiaoyu Liu.
Description: -In this correspondence, we propose a novel
method to extract illumination insensitive features for face
recognition under varying lighting called the gradient faces.
Theoretical analysis shows gradient faces is an illumination
insensitive measure, and robust to different illumination,
including uncontrolled, naturallighting.Inaddition,gradient
faces is derived from the image gradient domain such that it
can discover underlying inherent structure of face images
since the gradient domain explicitly considers the
relationships between neighboring pixel points. Therefore,
gradient faces has more discriminating power than the
illumination insensitive measure extracted from the pixel
domain. Recognition rates of 99.83% achieved on PIE
database of 68 subjects, 98.96% achieved on Yale B of ten
subjects, and 95.61% achieved on Outdoor database of 132
subjects under uncontrolled natural lightingconditionsshow
that gradient faces is an effectivemethod for facerecognition
under varying illumination. Furthermore, the experimental
results on Yale database validate that gradient faces is also
insensitive to image noise and object artifacts (such as facial
expressions).
Paper 2:- Student Attendance System in Classroom Using
Face Recognition Technique.
Author Name: -Samuel Lukas, Aditya Rama Mitra, Ririn
Ikana Desanti, Dion Krisnadi.
Description: -Authentication is one of the significant issues
in the era of information system.Amongother things,human
face recognition (HFR)isoneof known techniqueswhich can
be used for user authentication. As an important branch of
biometric verification, HFR has been widely used in many
applications, such as video monitoring/surveillancesystem,
human-computer interaction, and door access control
system and network security. This paper proposes amethod
for student attendance system in classroom using face
recognition technique by combining.
Author Name: -GuangzhengYang, Thomas SHuang.
Description: -The human face is a complex pattern. Finding
human faces automatically in a scene is a difficult yet
significant problem. It is the first important step in a fully
automatic human face recognition system. In this paper a
new method to locate human faces in a complex background
is proposed. This system utilizes a hierarchical knowledge-
based method and consists of three levels. The higher two
levels are based on mosaic images atdifferentresolutions.In
the lower level, an improved edge detection method is
proposed. In this research the problem of scale is dealt with,
so that the system can locate unknown human faces
spanning a wide range of sizes in a complex black-and-white
picture. Some experimental results are given.
Paper 4:-Study of Implementing Automated Attendance
System Using Face Recognition Technique.
Author Name: -Nirmalya Kar, Mrinal Kanti Debbarma,
Ashim Saha, and Dwijen Rudra Pal.
Description: -Authentication is a significant issue insystem
control in computer based communication. Human face
recognition is an important branch of biometric verification
and has been widely used in many applications, such as
video monitor system, human-computer interaction, and
door control system and network security. This paper
describes a method for Student’s Attendance System which
will integrate with the face recognition technology using
Personal Component Analysis (PCA) algorithm. The system
will record the attendance of the students in class room
environment automatically and it will provide the facilities
to the faculty to access the information of the studentseasily
by maintaining a log for clock-in and clock-out time.
IV. ARCHITECTURE

V. ALGORITHM
Viola and jones’s algorithm is used as the basis ofourdesign.
As we know there is some similarities in all human faces, we
used this concept as a haar feature to detect face in image.
Algorithm looks for specific haar feature of a face, if these
feature found algorithm pass the candidate to the next stage
.Here the candidate is not whole image but justa rectangular
part of this image known as sub window haveasizeof 24*24
pixel. With this window algorithm check whole image.
1. Haar Features
As we know there some kind of similarities in human face.
We use this concept for making haar feature .They are
composed of two or three rectangles. These features are
applied on face candidate to find out whether face is present
or not. Each haar feature has a value and this can be
calculated by taking the area of each rectangle and then
adding the result. Using the integral image concept we can
easily find out the area of rectangle.
2. Integral Image
The integral image is defined as the summation of the pixel
values of the original image. The valueatanylocation (x, y) of
the integral image is the sum of the image‟ s pixels above
and to the left of location (x, y). Fig. below illustrates the
integral image generation.
Fig: - Integral image
Fast Calculation in Integral Image
Fig. presents the calculation process:in ordertocalculate the
intensity sum of green region. Just four values of Fhavetobe
considered. As a consequence, the intensity sum of any
rectangular-shaped area can be calculated by considering as
few as four values of F. This allows for an extremely fast
calculation of a convolution with one of the rectangularhaar
feature describe above. The integral image F can be
calculated in pre-processing stage prior to detection in a
recursive manner in just one pass over the original image I
as in equation 2 and 3 below.
R(x, y) = R(x, y-1) + I(x, y) (2)
F(x, y) = F(x-1, y) + R(x, y) (3)
Where R and F are initialized by R(x, -1) = 0 and F (-1, y) =0.
The sum of intensities of a rectangular are ranging from (x,
y) to (x1, y1) can be calculated by considering the valuesof F
at the four cover point of the region instead of summing up
the intensities of all pixels inside:
3. Cascade
It is possible to eliminate the false candidate quickly using
stage cascading. The cascade eliminates candidate if it not
passed the first stage. If it passed than send it to next
stage.Which is more complicated than previous one. If a
candidate passed all the stage, this means a face is detected.
VI. OUTPUT
Fig: - Face Recognition Welcome page
Fig: -Registration

Fig: - Adding Face
Fig: - Attendance Report
VII. CONCLUSION
In order to take care of the attending this method has been
projected. It replaces the manual system with an automatic
system that is quick, efficient, price and time saving as
replaces the stationary material and therefore the paper
work. Thence this method is predicted togivedesired results
and in future can be enforced for logout. Also the efficiency
could be improved by integration alternative techniques
with it in close to future.
VIII. References
[1] A Study of Various Face Detection Method, Ms.Varsha
Gupta1 , Mr. Dipesh Sharma2,ijarccevol.3.
https://www.ijarcce.com/upload/2014/may/IJARCCE
7G.
[2] Attendance System Using Face Recognition and Class
Monitoring System, Arun Katara1, Mr. Sudesh2,
V.Kolhe3.
[3] G. Yang and T. S. Huang, Human face detection in
complex background, Pattern Recognition Letter, vol.
27, no.1, pp. 53-63,1994.
[4] C. Kotropoulos and I. Pitas,Rule-based facedetectionin
frontal views, Proc. Intl Conf. Acoustics, Speech and
Signal Processing, vol. 4, pp. 2537-2540, 1997.
[5] Xinjun Ma, Hongqiao Zhang, XinZang, A face detection
algorithm based on modified skincolor model, CCC, vol.
1, pp. 3896-3900, IEEE, 2013
[6] Naveed Khan Balcoh,M.HaroonYousaf, WaqarAhmand
M.IramBaig, Algorithm for efficient Attendance
Management: Face Recognition Based approach,
International Journal of Computer Science Issue, Vol.9,
Issue 4, No 1, July 2012.
[7] NirmalayaKar, MrinalKantiDebbarma,AshimSaha,and
DwijenRudraPal, Study of implementing Automated
Attendance System using Implementing Automated
Attendance System Using face recognition Technique,
International Journal of Computerand Communication
Engineering, Vol 1, No 2,July 2012
[8] O. Shoewn Development of Attendance Management
System using Biometrics. Pacific Journal of Scienceand
Technology Volume 13, No 1, May 2012
[9] M. Turk and A. Pentland (1991) Face recognition using
eigen faces. Proc.IEEEconference on computer vision
and Pattern Recognition.

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