Human-machine interaction issues in quality control based on online image classification
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Inspection of Stamped Sheet Metal Car Parts Using a Multiresolution Image Fusion Technique
ICVS '09 Proceedings of the 7th International Conference on Computer Vision Systems: Computer Vision Systems
On-line evolving image classifiers and their application to surface inspection
Image and Vision Computing
Assessment of the influence of adaptive components in trainable surface inspection systems
Machine Vision and Applications - Integrated Imaging and Vision Techniques for Industrial Inspection
Supervised and semi-supervised online boosting tree for industrial machine vision application
Proceedings of the Fifth International Workshop on Knowledge Discovery from Sensor Data
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In this paper, we present an automatic system designed for detect the presence of split defects in sheet-metal forming processes. The image acquisition system includes basically a CCD progressive camera and a diffuse illumination system mounted on the endeffector of a 6-dof robot. The inspection-robot displaces the image acquisition system over the pieces proceeding from the sheet-metal forming line. The recognition, positioning and the later inspection are realized as the pieces are moving on a conveyor belt. To realize the inspection, the acquired images are restored using a Markov random field model. Defect detection is carried out using an valley detection algorithm. To realize the recognition and to determine the precise position, we have used an Appearance- Based Method, based on a Principal Component Analysis (PCA).