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Method for segmentation of overlapping fish images in aquaculture

文献类型： 外文期刊

作者： Zhou, Chao 1 ; Lin, Kai 4 ; Xu, Daming 1 ; Liu, Jintao 1 ; Zhang, Song 1 ; Sun, Chuanheng 1 ; Yang, Xinting 1 ;

作者机构： 1.Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

2.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

3.Natl Engn Lab Agriprod Qual Traceabil, Beijing 100097, Peoples R China

4.Beijing Fisheries Res Inst, Beijing 100068, Peoples R China

5.Univ Almeria, Dept Comp Sci, Almeria 04120, Spain

关键词： aquaculture; image processing; overlapping segmentation; corner detection; improved Zhang-Suen algorithm ;

期刊名称：INTERNATIONAL JOURNAL OF AGRICULTURAL AND BIOLOGICAL ENGINEERING （ 影响因子：2.032； 五年影响因子：2.137 ）

ISSN： 1934-6344

年卷期： 2019 年 12 卷 6 期

页码：

收录情况： SCI

摘要： Individual fish segmentation is a prerequisite for feature extraction and object identification in any machine vision system. In this paper, a method for segmentation of overlapping fish images in aquaculture was proposed. First, the shape factor was used to determine whether an overlap exists in the picture. Then, the corner points were extracted using the curvature scale space algorithm, and the skeleton obtained by the improved Zhang-Suen thinning algorithm. Finally, intersecting points were obtained, and the overlapped region was segmented. The results show that the average error rate and average segmentation efficiency of this method was 10% and 90%, respectively. Compared with the traditional watershed method, the separation point is accurate, and the segmentation accuracy is high. Thus, the proposed method achieves better performance in segmentation accuracy and effectiveness. This method can be applied to multi-target segmentation and fish behavior analysis systems, and it can effectively improve recognition precision.

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