Multi-Workpiece Detection Algorithm Based on Corner Points and Triangular Centroid Distances
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    Abstract:

    In this paper, a triangular centroid distances (TCDs) descriptor that integrates corner information is proposed to solve the detection problem in the case of overlapping workpieces. The proposed descriptor detects the corner points and local contour direction of the target, which can be used to detect the suspected contour segments on the template contour. Then, the improved TCDs feature matrices are extracted from the target contour and the suspected contour segments of the templates. Finally, by calculating the distances between target contour matrix and each suspected contour feature matrix, the suspicious contour segment with the smallest distance can be determined as the corresponding workpiece. The experimental results showed that, not only recognition rate but also the efficiency of the proposed algorithm can be improved compared with traditional TCDs algorithm.

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SHEN Zheng, HU Chao. Multi-Workpiece Detection Algorithm Based on Corner Points and Triangular Centroid Distances[J]. Journal of Integration Technology,2021,10(3):12-21

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  • Received:
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  • Online: May 26,2021
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