An improved algorithm based on wellner’s threshold segmentation method

Abstract

According to the Wellner algorithm whose speed is slow and the image threshold is not smooth for computing a large amount of defects, this paper presents two kinds of improved scheme, the first scheme is one dimensional smoothing algorithm (ODSA), the second is based on the first one and its name is integral image algorithm(IIA). The former one mainly considering the spatial relationship between pixels, to ensure the continuity of pixels after segmentation; the latter dynamically set local threshold according to different environmental, to avoid local all black or all white, to separated object from the background exactly. Through the contrast experiment, its results show that, Wellner algorithm is not ideal at the edge of image processing, and the time complexity is too high. The one-dimensional smoothing algorithm is clear and accurate when processing contour, but the time complexity is relatively large. When we use the integral image algorithm to processing image, the foreground and background segmentation is clear, and the error rate is very low, and the time complexity is minimum, and it has good ability to adapt to the scene, so the integral image algorithm is the best.