چکیده (انگلیسی):

Video surveillance is an important aspect in today’s world, where a particular scene of area requires
monitoring to avoid terrorist attacks and unauthorized entries. Vehicle recognition is an important area in
object tracking and recognition. Objects may be of rigid or non-rigid in nature with varying velocity and
have different features. Important features like shape, logo, color and texture are complex in nature.
Hence there is a need of better algorithm for detecting and identifying the objects like car. A new method
is proposed for recognizing the cars present in the video. At first the features like shape is extracted using
moments, logo using the Scale Invariant Feature Transform (SIFT) and the RGB color values of the car
body. Using these features the recognition is carried out to classify the type of car. Recognition of cars
has range of application like, military surveillance, traffic management, autonomous navigation system,
auto parking.