A fast circle detection method based on threshold segmentation and validity check for FPC images

Flexible printed circuit board (FPC) is a popular substrate for packaging integrated circuits (ICs). Detecting the circles rapidly on FPCs by using computer vision is very important to assess the quality of FPCs during its manufacturing. In this paper, a fast circle detection approach based on a threshold segmentation method and a validation check is proposed. In the algorithm, the image is firstly segmented by an adaptive heuristic threshold to obtain closed contours; then circle candidates are obtained by eliminating obvious non-circle contours; and at last, circle candidates are further validated to be circles according to Helmholtz principle. Experimental results show that the proposed method is very fast and has high detection rates to detect the circles on FPC images.

[1]  Sonja Grgic,et al.  Shape analysis and classification of masses in mammographic images using neural networks , 2011, 2011 18th International Conference on Systems, Signals and Image Processing.

[2]  Sankar K. Pal,et al.  Theoretical quantification of shape distortion in fuzzy Hough transform , 2005, Fuzzy Sets Syst..

[3]  Erkki Oja,et al.  A new curve detection method: Randomized Hough transform (RHT) , 1990, Pattern Recognit. Lett..

[4]  Kuo-Liang Chung,et al.  An Efficient Randomized Algorithm for Detecting Circles , 2001, Comput. Vis. Image Underst..

[5]  Jean-Michel Morel,et al.  From Gestalt Theory to Image Analysis: A Probabilistic Approach , 2007 .

[6]  Cuneyt Akinlar,et al.  EDCircles: A real-time circle detector with a false detection control , 2013, Pattern Recognit..

[7]  B. Soheilian,et al.  CIRCULAR ROAD SIGN EXTRACTION FROM STREET LEVEL IMAGES USING COLOUR, SHAPE AND TEXTURE DATABASE MAPS , 2009 .

[8]  Rafael Grompone von Gioi,et al.  LSD: A Fast Line Segment Detector with a False Detection Control , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Jean-Michel Morel,et al.  Gestalt Theory and Computer Vision , 2004 .

[10]  Zhang Guangjun Radius Constraint Least-square Circle Fitting Method and Error Analysis , 2006 .

[11]  Jitendra Malik,et al.  Using contours to detect and localize junctions in natural images , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[12]  Bidyut Baran Chaudhuri,et al.  A survey of Hough Transform , 2015, Pattern Recognit..

[13]  Magnus Andersson,et al.  A fast and robust circle detection method using isosceles triangles sampling , 2016, Pattern Recognit..

[14]  Jiun-Jian Liaw,et al.  An effective voting method for circle detection , 2005, Pattern Recognit. Lett..