Target Verification via Novel Adaptive Segmentation Used to Detect and Track Moving Objects

It is an original study to integrate the utmost activities and academic research. In this research, a new image segmentation (NIS) is present to search object information for initial target verification in the region of interest (ROI) area in global histogram. After that adaptive singular value decomposition (ASVD) is combined to suppress variation in lighting for color images. HSV color model integrates computer vision techniques made to fit the dynamic environments for object detection. In addition, several tracking algorithms are applied to estimate and track the activity data. Experimental results show that the objects could successfully detect and track the sequence of images, performance and the tracking rate in accordance with accurate Kalman filter (HSV) which is better than the other algorithms.