A new adaptive object detection technique based on the wavelet co-occurrence features

摘要

This Object detection involves processing images for detecting, classifying, and tracking targets embedded in a background scene. This paper presents an adaptive algorithm for detecting a specified target objects embedded in visual images for tracking application. The developed algorithm employs a novel technique using the wavelet co-occurrence features for detecting object based on template matching. Several signatures as contrast, energy, entropy and maximum probability are computed from wavelet co-occurrence features for object window and compares with features of image windows. The results of the proposed algorithm are very adaptive in variant condition with clutters