Multiple contour sequences' segmentation and entity recognition methods in vision measurement

Feng Yang; Shoubin Liu

doi:10.1117/12.917812

15 November 2011 Multiple contour sequences' segmentation and entity recognition methods in vision measurement

Feng Yang, Shoubin Liu

Proceedings Volume 8335, 2012 International Workshop on Image Processing and Optical Engineering; 83351M (2011) https://doi.org/10.1117/12.917812
Event: 2012 International Workshop on Image Processing and Optical Engineering, 2012, Harbin, China

Abstract

In this paper, an approach is proposed for segmentation of multiple contour sequences and recognition of entities for vision measurement of small precision parts. The approach includes several steps as follows. All contour sequences of the part are detected at the first place. Secondly, a circle identification method is used to find circular contours in contour sequences. The identified circular contours are further fitted as individual circles. Then, curvature method is selected to detect dominant points in the rest contours and height projection method is adopted to classify them as line or arc entities. In the end, the least-squares method is used to merge and add dominant points. Experimental results show lines, arcs and circles can be recognized satisfactorily by using the approach presented.

Citation Download Citation

Feng Yang and Shoubin Liu "Multiple contour sequences' segmentation and entity recognition methods in vision measurement", Proc. SPIE 8335, 2012 International Workshop on Image Processing and Optical Engineering, 83351M (15 November 2011); https://doi.org/10.1117/12.917812

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