Laser & Optoelectronics Progress, Volume. 57, Issue 8, 081004(2020)
Machine Vision Based Detection Method for Surface Crack of Ceramic Tile
Fig. 1. Image of ceramic tile. (a) Crack image; (b) surface gray distribution map
Fig. 2. Process of surface crack detection of ceramic tile based on PCA method. (a) Red channel image of ceramic tile; (b) results of sample centralization; (c) covariance matrix of centralization matrix displays with two-dimensional image; (d) projection matrix displays with two-dimensional image; (e) dimension-reduced post-sample matrix displays with two-dimensional image; (f) reconstruction of h=20; (g) results of difference between graph (f) and graph (a); (h) results of crack detection
Fig. 3. Effect of principal component h on defects. (a) Red channel image of ceramic tile; (b) h=10 reconstruction image; (c) h=15 reconstruction image; (d) h=20 reconstructed image; (e) h=25 reconstructed image; (f) h=30 reconstructed image
Fig. 4. Crack detection process of ceramic tile in texture area. (a) Red channel image of ceramic tile; (b) h=20 reconstruction image; (c) result of difference between graph (b) and graph (a); (d) result of crack detection
Fig. 5. Test results of different algorithms. (a) Red channel image of ceramic tile; (b) Canny operator; (c) discrete wavelet transform; (d) automatic area growth; (e) our algorithm
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Qiang Li, Shuguang Zeng, Sheng Zheng, Yanshan Xiao, Shaowei Zhang, Xiaolei Li. Machine Vision Based Detection Method for Surface Crack of Ceramic Tile[J]. Laser & Optoelectronics Progress, 2020, 57(8): 081004
Category: Image Processing
Received: Jul. 31, 2019
Accepted: Sep. 6, 2019
Published Online: Apr. 3, 2020
The Author Email: Zeng Shuguang (zengshuguang@163.com)