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A classical approach for thinning of binary images using divergence of the potential field. (English) Zbl 1076.94507

Summary: An algorithm for thinning of an object from its binary image is described. A generalized potential field is defined over the interior of the object and the divergence of the corresponding vector field is computed for each interior pixel. Then, those pixels of the object whose divergence values are above some specified threshold are selected, resulting in a thinned version of the original object. The density of the resulting skeletal structure can be controlled using different threshold values. The thinned version of the object obtained by this method can be used for image compression and shape matching.

MSC:

94A08 Image processing (compression, reconstruction, etc.) in information and communication theory
68U10 Computing methodologies for image processing

Software:

Powercrust
Full Text: DOI

References:

[1] Saraf, Y., Balasubramanian, R. and Swaminathan, K. Computing the curve-skeletons of images. Proceedings of the 8th World Multi-Conference on Systemics, Cybernetics and Informatics. Vol. 12, pp.310–315. Orlando, Florida · Zbl 1140.68528
[2] DOI: 10.1109/TPAMI.1985.4767685 · doi:10.1109/TPAMI.1985.4767685
[3] DOI: 10.1016/0262-8856(93)90055-L · doi:10.1016/0262-8856(93)90055-L
[4] Blum H., Models for the Perception of Speech and Visual Form pp 362– (1967)
[5] Amenta, N., Choi, S. and Kolluri, R. K. The power crust. Proceedings of the 6th ACM Symposium on Solid Modeling. pp.249–260. New York: ACM Publications. · Zbl 0988.65015
[6] DOI: 10.1109/34.574801 · doi:10.1109/34.574801
[7] DOI: 10.1006/gmip.1999.0495 · doi:10.1006/gmip.1999.0495
[8] Gagvani, N. 2001. ”Parameter-controlled skeletonization–a framework for volume graphics”. New Brunswick, NJ: Rutgers University. PhD Thesis
[9] DOI: 10.1109/34.107013 · doi:10.1109/34.107013
[10] Tsao, Y. F. and Fu, K. S. A 3D parallel skeletonization thinning algorithm. IEEE Pattern Recognition and Image Processing Conference. pp.678–683. New York: IEEE Computer Society Press.
[11] DOI: 10.1023/A:1023335904573 · Zbl 1039.68160 · doi:10.1023/A:1023335904573
[12] DOI: 10.1109/34.888709 · doi:10.1109/34.888709
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