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Machine vision based automatic apparatus and method for surface defect detection
- Source :
- 2018 13th World Congress on Intelligent Control and Automation (WCICA).
- Publication Year :
- 2018
- Publisher :
- IEEE, 2018.
-
Abstract
- Machine vision based automatic apparatus is a necessary component of an automated production line. In this paper, taking can-end surface defect detection as an example, we presented a visual inspector and proposed a new surface defect detection framework. Firstly, the Region of Interest (ROI) of the input image is got by circle detection and prior radius knowledge of can-end. Then, the saliency map and texture filtering image are computed to overcome the problems of irregular texture and non-uniform illumination. Finally, all suspected defects are obtained by saliency map segmentation, connected component analysis. Following, the size, the average saliency value and the mean texture filtering value of each suspected defective region are calculated, and the 3-dimensional features are used to distinguish true defects in the central panel region of can-end. We employ the designed equipment to grab can-end images and do tests divided into four groups on the grabbed images. The accuracy is 98.16% and the execution time is about 65.7 milliseconds. Experimental results demonstrate that the proposed method can inspect faint and low contrast defect accurately. Meanwhile, the proposed method is simple and computationally efficient and meets the high speed of industrial automation.
- Subjects :
- 0209 industrial biotechnology
business.industry
Texture (cosmology)
Machine vision
Computer science
020208 electrical & electronic engineering
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
02 engineering and technology
020901 industrial engineering & automation
Region of interest
Texture filtering
0202 electrical engineering, electronic engineering, information engineering
Computer vision
Saliency map
Segmentation
Artificial intelligence
business
Connected-component labeling
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2018 13th World Congress on Intelligent Control and Automation (WCICA)
- Accession number :
- edsair.doi...........96dede05c9b35523c5a84d6883b6ad6a