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Object segmentation using graph cuts and active contours in a pyramidal framework
Author(s): Priyambada Subudhi; Susanta Mukhopadhyay
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Paper Abstract

Graph cuts and active contours are two very popular interactive object segmentation techniques in the field of computer vision and image processing. However, both these approaches have their own well-known limitations. Graph cut methods perform efficiently giving global optimal segmentation result for smaller images. However, for larger images, huge graphs need to be constructed which not only takes an unacceptable amount of memory but also increases the time required for segmentation to a great extent. On the other hand, in case of active contours, initial contour selection plays an important role in the accuracy of the segmentation. So a proper selection of initial contour may improve the complexity as well as the accuracy of the result. In this paper, we have tried to combine these two approaches to overcome their above-mentioned drawbacks and develop a fast technique of object segmentation. Here, we have used a pyramidal framework and applied the mincut/maxflow algorithm on the lowest resolution image with the least number of seed points possible which will be very fast due to the smaller size of the image. Then, the obtained segmentation contour is super-sampled and and worked as the initial contour for the next higher resolution image. As the initial contour is very close to the actual contour, so fewer number of iterations will be required for the convergence of the contour. The process is repeated for all the high-resolution images and experimental results show that our approach is faster as well as memory efficient as compare to both graph cut or active contour segmentation alone.

Paper Details

Date Published: 5 March 2018
PDF: 8 pages
Proc. SPIE 10714, Third International Conference on Photonics Solutions (ICPS2017), 107140B (5 March 2018); doi: 10.1117/12.2299627
Show Author Affiliations
Priyambada Subudhi, Indian Institute of Technology (Indian School of Mines) (India)
Susanta Mukhopadhyay, Indian Institute of Technology (Indian School of Mines) (India)


Published in SPIE Proceedings Vol. 10714:
Third International Conference on Photonics Solutions (ICPS2017)
Thawatchai Mayteevarunyoo, Editor(s)

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