A novel traffic-tracking system using morphological and Blob analysis

A vision-based pedestrian and car tracking system which is able to distinguish between car and pedestrian is possible using Morphological processing and Blob analysis. Videos are sequence of image frames. Here the algorithm is developed to analyse a frame and the same will be applied to all frames in a video. The unwanted objects in video frame can be removed by converting colour frames into a gray scale and by applying thresholding algorithm. Threshold can be set depending on the object to be detected. Gray scale image will be converted to binary during thresholding process. Morphological processing will be applied on binary image to remove small unwanted objects that are presented in a frame. A developed blob analysis technique for extracted binary image facilitates pedestrian and car detection. Processing blob's information of relative size and location leads to distinguishing between pedestrian and car. The threshold, morphological and blobs process is applied to all frames in a video and finally original video with tagged cars will be displayed.