Wei Jian
College of Computer and Information, China Three Gorges University, Yichang 443000, ChinaYang Shanshan
2.Three Gorges Mathematical Research Center,China Three Gorges University,Yichang 443000, China； 3.College of Science, China Three Gorges University, Yichang 443000, ChinaZheng Sheng
2.Three Gorges Mathematical Research Center,China Three Gorges University,Yichang 443000, China； 3.College of Science, China Three Gorges University, Yichang 443000, ChinaXia Yongqi
College of mechanical and power engineering, China Three Gorges University,Yichang 443000, ChinaZeng Shuguang
College of Science, China Three Gorges University, Yichang 443000, China1.College of Computer and Information, China Three Gorges University, Yichang 443000, China; 2.Three Gorges Mathematical Research Center,China Three Gorges University,Yichang 443000, China; 3.College of Science, China Three Gorges University, Yichang 443000, China; 4.College of mechanical and power engineering, China Three Gorges University,Yichang 443000, China
TP391
Defect detection on ceramic tile surface is an indispensable process during its production. To meet the needs of automatic detection, this paper proposes an algorithm which is based on adaptive wavelet transform, to perform defect bulge detection on ceramic tile surface with complex stereoscopic texture interference. Firstly, the red channel image of the ceramic tile is extracted and preprocessed by Gaussian filtering to suppress noise. Secondly, adaptive wavelet transform and linear median filtering are used to enhance the contrast between the bulge and the background area. Finally, the methods of binarization and morphology are applied to obtain the information of the bulge area. It is noted that the algorithm can detect the bulging defects of ceramic tiles of complex three-dimensional texture, with an accuracy of up to 98.5% and recall rate over 95%.
