Improving Watershed Algorithm with a Histogram Driven Methodology and Implementation of the System on a Virtex 5 Platform

Abstract

Watershed algorithm as was introduced by Vincent and Soille is a segmentation algorithm based on the inundation process of the image gradient which is observed as a relief. It aims at finding the peaks in the image gradient called watersheds and identifying them as the image contours. Due to its flexibility and rapidity, this algorithm is used in several applications. However, its main drawback is the over segmentation .In this paper, we improve this technique by introducing a histogram driven methodology. The developed architecture is applied on an empirical basis for research on image segmentation and boundary detection in order to be compared with other segmentation algorithms. The simulation results show that the performance of our algorithm is superior to the other segmentation techniques. Finally, the whole design is implemented on a Virtex 5 platform based on a codesign methodology leading to 147 MHz frequency and 76% of hardware resource occupation for an image of the size of 128*128.

Sky segmentation with ultraviolet images can be used for navigation

“…A histogram is computed from the intensity image, excluding the darkest and brightest 2 percent of pixels, and the adapted-watershed algorithm described in [30] is applied until only two segments of the histogram remain. The intensity value midway between the closest points of the two histogram segments is then set as the threshold for ground/sky segmentation.…”