Image segmentation based on SOFM in camouflage design

Miao Chu; Mengying Zhuang; Tianhui Sun

doi:10.1117/12.2557181

3 January 2020 Image segmentation based on SOFM in camouflage design

Miao Chu, Mengying Zhuang, Tianhui Sun

Proceedings Volume 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019); 113731E (2020) https://doi.org/10.1117/12.2557181
Event: Eleventh International Conference on Graphics and Image Processing, 2019, Hangzhou, China

Abstract

Camouflage pattern design is supposed to simulate natural background with using several colors. Therefore, in order to design camouflage patterns automatically, texture feature of background image is extracted by image segmentation technologies which is the hot topic in camouflage research field recently. Image mean-clustering segmentation is the most common method of image segmentation; however it is easily to lose image details due to using of pixel-value differences directly. To solve the deficiency of the mean clustering segmentation in existence, the image segmentation method based on SOFM is proposed in this paper, combined with the technology of artificial intelligence network learning, it can retain the more details of the image, and make up the deficiencies of mean clustering method.

Citation Download Citation

Miao Chu, Mengying Zhuang, and Tianhui Sun "Image segmentation based on SOFM in camouflage design", Proc. SPIE 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019), 113731E (3 January 2020); https://doi.org/10.1117/12.2557181

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