Image segmentation of Huaniu apple based on pulse coupled neural
network and watershed algorithm

Qing Liu; Xiaolong Zhao; Hongping Yang; Limin Zhao; Weijun Ling; Xiaoshu Ma; Feiping Lu; Yuxiang Zhao

doi:10.1117/12.2634516

4 May 2022 Image segmentation of Huaniu apple based on pulse coupled neural network and watershed algorithm

Qing Liu, Xiaolong Zhao, Hongping Yang, Limin Zhao, Weijun Ling, Xiaoshu Ma, Feiping Lu, Yuxiang Zhao

Author Affiliations +

Proceedings Volume 12172, International Conference on Electronic Information Engineering and Computer Communication (EIECC 2021); 121721X (2022) https://doi.org/10.1117/12.2634516
Event: International Conference on Electronic Information Engineering and Computer Communication (EIECC 2021), 2021, Nanchang, China

Abstract

It is the key step of automatic apple picking and sorting to segment of the apple image in natural environment using image information processing technology. In order to improve the intellectualization of apple picking process and effectively extract the target of image segmentation, a novel image segmentation method of Huaniu apple based on pulse coupled neural network (PCNN) and watershed algorithm is proposed. Firstly, the PCNN model is improved and optimized on the basis of image RGB to L*A*B space conversion. Then, the improved PCNN combined with watershed algorithm was used to segment the apple image on considering the image texture and color feature information. The theoretical analysis and experimental results show that the novel method is effectively able to segment target image, and can preserve the image details and the edges as well. The proposed algorithm has better subjective vision effect and objective quality than the traditional watershed and other related algorithms.

Citation Download Citation

Qing Liu, Xiaolong Zhao, Hongping Yang, Limin Zhao, Weijun Ling, Xiaoshu Ma, Feiping Lu, and Yuxiang Zhao "Image segmentation of Huaniu apple based on pulse coupled neural network and watershed algorithm", Proc. SPIE 12172, International Conference on Electronic Information Engineering and Computer Communication (EIECC 2021), 121721X (4 May 2022); https://doi.org/10.1117/12.2634516

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