  Object recognition is a critical part of any surveillance system. It is the
matter of utmost concern to identify intruders and foreign objects in the area
where surveillance is done. The performance of surveillance system using the
traditional camera in daylight is vastly superior as compared to night. The
main problem for surveillance during the night is the objects captured by
traditional cameras have low contrast against the background because of the
absence of ambient light in the visible spectrum. Due to that reason, the image
is taken in low light condition using an Infrared Camera and the image is
enhanced to obtain an image with higher contrast using different enhancing
algorithms based on the spatial domain. The enhanced image is then sent to the
classification process. The classification is done by using convolutional
neural network followed by a fully connected layer of neurons. The accuracy of
classification after implementing different enhancement algorithms is compared
in this paper.
