標題: AUTOMATIC INSPECTION SYSTEM FOR DEFECTS OF PRINTED ART TILE BASED ON TEXTURE FEATURE ANALYSIS
作者: Yang, Shih-Wei
Lin, Chern-Sheng
Lin, Shir-Kuan
Tseng, Yung-Chin
電控工程研究所
Institute of Electrical and Control Engineering
關鍵字: defect classifier;gray level co-occurrence matrix;printed art tile
公開日期: 2-一月-2014
摘要: An automatic inspection system of printed art tile defects is reported in this artucke. After calculating eight defect features of art tile using the gray level co-occurrence matrix and the average R, G, B values of a defective area, the results were input into a backward propagation neural network for training the defect classifier. During inspection, the proposed system compared the inspected image with a standard image and removed noise by an erosion operation in order to preliminarily determine whether the art tile had defects. For the defective art tile images, the proposed classifier successfully identified four types of common printing defects. The proposed algorithm had an average recognition rate of 90%, suggesting that the recognition accuracy is good, and only requires 1-2s to inspect an art tile with the size of 15x15cm(2). The inspection speed is faster than the conventional manual inspection, and recognition results are more stable. The proposed system can reduce the risk of error caused by the long duration of manual inspection, and thus, can reduce manufacturing costs.
URI: http://dx.doi.org/10.1080/10739149.2013.836659
http://hdl.handle.net/11536/23193
ISSN: 1073-9149
DOI: 10.1080/10739149.2013.836659
期刊: INSTRUMENTATION SCIENCE & TECHNOLOGY
Volume: 42
Issue: 1
起始頁: 59
結束頁: 71
顯示於類別:期刊論文


文件中的檔案:

  1. 000327296000006.pdf