Vehicle Detection and License Plate Recognition System

Moving object detection is an important process in most video-based applications such as video surveillance, traffic monitoring, human motion capture, etc. Background subtraction and color image segmentation methods are widely used for detecting moving objects in a video stream that help detecting features of the moving object for further video processing. In this paper, moving object detection system is proposed based on both background subtraction, color segmentation, license plate recognition methods. This method builds a background model and normally distributed each pixel in the image sequences and calculating the difference between each image in the sequence and this background model for foreground extraction and detecting movement areas from the background model and then the background model is updated. Color segmentation is applied to separate features based on colors. The system detects vehicles enter parking gate and allow only a specific vehicle type depending on vehicle color and license plate. License plate recognition depending on vehicle type is implemented after color segmentation. Experimental results of implementing the proposed method using video sequences provided by surveillance camera show superior performance and the system detects moving objects successfully.