Robust fully-automatic segmentation based on modified edge-following technique

The paper proposes a robust fully-automatic segmentation scheme based on a modified edge-following technique. First, an image frame is partitioned into many B×B-pixel blocks. In each block, the pixel point having the maximum gray-level difference from its neighboring point can be selected as the initial point. Additionally, the threshold can be determined automatically according to the histogram of gray-level difference values of initial points with their neighboring points. By using this threshold value, the edge points are determined from the initial points. Based on edge points, the modified edge-following technique with multiple direction detections is performed to find the closed-loop contours. The whole process is fully automatic, so that the disadvantages of both snake and live wire on the fly (LWOF) schemes on manually selecting the initial contours and points, and of the watershed on manually setting the threshold value can be dramatically improved at the same time. Owing to the rapid and fully-automatic segmented results, the proposed scheme is more robust and applicable on various image and video applications than conventional segmentation schemes.