Application of an improved watershed algorithm based on distance map reconstruction in bean image segmentation

作者：Hongquan Liu, Weijin Zhang, Fushun Wang, Xiaohua Sun, Junhao Wang, Chen Wang, Xinxin Wang · 发表于：Heliyon · 年份：2023 · DOI：10.1016/j.heliyon.2023.e15097 · 被引用次数：21 · 研究领域：Smart Agriculture and AI、Industrial Vision Systems and Defect Detection、Spectroscopy and Chemometric Analyses

As an important step in image processing, image segmentation can be used to determine the accuracy of object counts, and area and contour data. In addition, image segmentation is indispensable in seed testing research. Due to the uneven grey level of the original image, traditional watershed algorithms generate many incorrect edges, resulting in oversegmentation and undersegmentation, which affects the accuracy of obtaining seed phenotype information. The DMR-watershed algorithm, an improved watershed algorithm based on distance map reconstruction, is proposed in this paper. According to the grey distribution characteristics of the image, the grey reduction amplitude h was selected to generate the mask image with the same grey distribution trend as that of the original image. The original greyscale map was reconstructed with corresponding thresholds selected according to the false minima of different regions that are to be segmented, which generates an accurate distance map that eliminates the wrong edges. An adzuki bean ( Vigna angularis L.) image was selected as the experimental material and the residual rate of the segmentation counting results of each algorithm was investigated in two cases of two-particle adhesion and multiparticle adhesion. The results of the proposed algorithm were compared with those of the traditional watershed algorithm, edge detection algorithm and concave point analysis algorithm which are commonly used for seed segmentation. In the case of two-pa...