An Improved Otsu Method Based on Uniformity Measurement for Segmentation of Water Surface Images

作者：Ning Li, Xin Lv, Bo Li, Shoukun Xu · 年份：2019 · DOI：10.1109/ithings/greencom/cpscom/smartdata.2019.00129 · 被引用次数：7 · 研究领域：Image Enhancement Techniques、Oil Spill Detection and Mitigation、Remote Sensing and LiDAR Applications

One-dimensional Otsu method is an adaptive threshold method which obtains the optimal threshold for image segmentation by the maximum between-class variance. Direct application of the Otsu segmentation method is very challenging due to the uniform background of the water surface image. In this paper, we propose an improved Otsu method based on uniformity measurement for segmentation of water surface. It achieves adaptive selection of thresholds by the uniformity measure function, so as to segment the surface floating object area better. Experimental results demonstrate that the effectiveness of the improved Otsu method is generally better than traditional Otsu method for the water surface images, which greatly improves the segmentation accuracy of images and reduces the mis-segmentation rate.