Edge and texture detection of metal image under high temperature and dynamic solidification condition

• Published in: Journal of Central South University Vol. 25; no. 6; pp. 1501 - 1512
• Main Authors: Chen, Zu-guo, Li, Yong-gang, Chen, Xiao-fang, Yang, Chun-hua, Gui, Wei-hua
• Format: Journal Article
• Language: English
• Published: Changsha Central South University 01.06.2018; Springer Nature B.V
• Subjects: Adaptive algorithms; Algorithms; Convolution; Cube texture; Engineering; Entropy; High temperature; Image detection; Interpolation; Mathematical analysis; Metallic Materials; Pixels; Solidification; 金属图像; metal image; GEAF-CCI 算法; 边缘与纹理检测; DTMLGE 算法; GEAF-CCI algorithm; DTMLGE algorithm; edge and texture detection
• ISSN: 2095-2899; 2227-5223
• DOI: 10.1007/s11771-018-3843-3

The zinc casting is a complicated process with high temperature, high dust content and dynamic solidification. To accurately detect the edge and texture of metal image under this condition, a sub-pixel detection based on gradient entropy and adaptive four-order cubic convolution interpolation (GEAF-CCI) algorithm is proposed. This method mainly involves three procedures. Firstly, the gradient image is generated from the grey images by using gradient operator. Then, a dynamic threshold based on the maximum local gradient entropy (DTMLGE) algorithm is applied to distinguishing the edge and texture pixels from gradient images. Finally, the adaptive four-order cubic convolution interpolation (AF-CCI) algorithm is proposed for interpolating calculation of the target edges and textures according to their variation differences in different directions. The experimental result shows that the proposed algorithm can remove the jag and blur of the edges and textures, improve the edge positioning precision and reduce the false or missing detection rate.