Human Face Detection And Recognition Using Web Cam

1996 words - 8 pages

Journal of Computer Science 8 (9): 1585-1593, 2012
ISSN 1549-3636
© 2012 Science Publications
Human Face Detection and Recognition using Web-Cam
Petcharat Pattanasethanon and Charuay Savithi
Depatment of Business Computer, Faculty of Accountancy and Management,
Mahasarakham UniversityKamreang, Kantharawichai, Mahasarakham 44150, Thailand
Abstract: Problem statement: The illuminance insensitivity that reflects the angle of human facial
aspects occurs once the distance between the object and the camera is too different such as animated
images. This has been a problem for facial recognition system for decades. Approach: For this reason,
our study represents a novel technique for ...view middle of the document...

From most video files, blurry lighting
has made it a disadvantage to identify facial clarity
(Agarwal et al., 2010). In a constantly moving
environment such as personal vehicles, only certain
parts of the overall facial are captured. Therefore, it is
even more demanding to develop a capture model and
recognition model from Web-Cams (Zhu et al., 2010).
However, in this study, we have developed a model
that provides the solution for both models to be met.
There are two critical stages for the model to follow,
which are the Facial Detection stage and the Facial
Recognition stage. The purpose of this research is to
develop a facial recognition model which can
accurately predict or match the subject's image from
our database. Input image can be either from the
camera storage or the database itself. The essential
parts of human facial characteristics consist of eyes,
nostril shapes, mouth shapes and skin. After the input
image is uploaded, we set the limitation for its edged,
compute for the area of human skin, crop the facial
shape into and eclipse shape, convert the color into
greyscale and normalize the color to reduce color
complexities (Micael et al., 2007). The image or data is
then transformed using Successes Mean Quantization
Transform (SMQT) technique and match with the
database referencing the similarity measurement of
both images. Nonetheless, if the image does not exist in
the database, the input data will be kept in the database
and the system will notify the user. On the other hand,
if the image exists in our database, the system will
compute for similarity measurement from the
Euclidean Distance of the image exist in our database.
Crimes, homicides and assaults are literally the primary
problems of various countries. In some countries,
social security is not provided equally to the entire
population due to the low financial support for such
over-prized system (Paschalakis and Bober, 2003). Our
work supports low cost and highly productive system
in order to assist organizations such as government,
retails, shopping centers, or even private businesses
that require sufficient security provider. The other
aspect that this system took advantage of is the
difference in facial characteristics of human. The
interesting part is that we humans have different
biological characteristics that are hardly changed or
implanted physically. Besides, it is a multitasking
system that user does not have to physically touch the
Corresponding Author: Petcharat Pattanasethanon, Depatment of Business Computer, Faculty of Accountancy and Management,
Mahasarakham UniversityKamreang, Kantharawichai, Mahasarakham 44150, Thailand
1585
J. Computer Sci., 8 (9): 1585-1593, 2012
equipment or yield from doing other activities, since it
will detect the subject automatically that the subject
does not know that he or she is being captured. We can
easily agree on the benefits of facial recognition
models, however, there...

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