A Watershed Image Segmentation Algorithm Based on Self-adaptive Marking and Interregional Affinity Propagation Clustering

作者：Cai Qiang; Liu Ya-Qi^*; Cao Jian; Li Hai-Sheng; Du Jun-Ping

来源：Acta Electronica Sinica, 2017, 45(8): 1911-1918.

DOI：10.3969/j.issn.0372-2112.2017.08.015

• Affinity propagation
• Affinity propagation clustering
• Over segmentation
• Region based image segmentation
• Self-adaptive marking
• State-of-the-art methods
• Water-shed algorithm
• Watershed image segmentation

The watershed algorithm can conduct region-based image segmentation effectively and accurately, but it tends to cause over-segmentation. To tackle the above mentioned problem, an improved watershed algorithm is proposed, as follows:first of all, the color gradient is computed using spectrum envelope filtered color image, based on which, regions with minimum gradient are marked using self-adaptive H-minima transformation method. Then, the watershed transform is applied to segment the marked gradient image. Finally, affinity propagation clustering is adopted to merge the regions segmented by the watershed transform, using color moments computed on each local region, to get the final segmentation result. Experiments conducted on public available datasets demonstrate the adaptability and robustness of proposed algorithm, compared with the relative state-of-the-art methods. The proposed method can solve the over-segmentation problem well and get accurate results.

• 出版日期2017
• 单位中国科学院大学; 北京大学