Micro-Object Detection by Dynamic ROI Combined with Pyramid Template Matching

This paper introduces a new detection method of objects in micro-scale based on dynamic region of interest (ROI) method combined with pyramid template matching (PTM) approach. The dynamic ROI method works based on the position predicting, which is provided by the Kalman filter (KF). Rather than searching the entire image, the detection ROI is located at a limited region. Experimental results show that the detected positions match well with the real motion path. Moreover, the dynamic ROI method reduces the computation time by 30% as compared with the PTM algorithm.