Transactions of Materials and Heat Treatment

Title：Image segmentation algorithm on contour defects for stamping part based on improved MRF

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ClassificationCode：TP391.41；TG84

year,vol(issue):pagenumber：2022,47(4):101-109

Abstract：

For the problem of visual inspection for surface defects of stamping part during the production process, an improved Markov Random Field (MRF) image segmentation algorithm was proposed. First, the pixel-based MRF algorithm was applied to obtain the pixel features and extract the pixel-based likelihood function, and the stochastic region merging algorithm was used to obtain regional features, and the likelihood function based on stochastic region merging was extracted. Then, the edge features of the image was obtained by the maximum gradient algorithm, and the edge-based likelihood function was extracted to restore the edge information lost in the stochastic region merging process. Furthermore, three kinds of likelihood functions were fused, and image segmentation was realized by the minimum energy criterion. Finally, the effectiveness of the algorithm was verified by comparative experiments with traditional image segmentation methods. The experimental results show that the improved algorithm can achieve accurate segmentation of stamping part images, and the application effect is better.

Funds：

扬州市“绿扬金凤计划”高层次创新创业领军人才引进项目（2021CX044）

作者简介：吕宁(1970-)，男，工学博士，教授，研究生导师 E-mail：ning_lv@163.com 通信作者：肖剑(1996-)，男，硕士研究生 E-mail：moqizixi@163.com

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