Dayanand S. Shilwant,Dr. A.R.Karwankar
Download PDFImage processing is widely used in many
applications, including medical imaging, industrial
manufacturing, and security systems. Often the size of image
is very large, the processing time has to be small and usually
real time constrains have to be met. Therefore, during the
last decades their has been an increasing interest in the
development and use of parallel algorithms in image
processing.In this paper, we propose a system that takes the
attendance of students in classroom automatically using face
detection and face recognition. However, it is difficult to
estimate the attendance precisely using each result of face
recognition independently because the face detection rate is
not sufficiently high. In this paper, we propose a method for
estimating the attendance precisely using all the results of
face recognition obtained by continuous observation.
Continuous observation improves the performance for the
estimation of the attendance.We constructed the lecture
attendance system based on face recognition, and applied the
system to classroom lecture. This paper first review the
related works in the field of attendance management and face
recognition. Then, it introduces our system structure and
plan. Finally, experiments are implemented to provide as
evidence to support our plan. The result shows that
continuous observation improved the performance for the
estimation of the attendance.
