Image Segmentation by Stochastic Active Contour.

Date of Submission

December 2005

Date of Award

Winter 12-12-2006

Institute Name (Publisher)

Indian Statistical Institute

Document Type

Master's Dissertation

Degree Name

Master of Technology

Subject Name

Computer Science


Electronics and Communication Sciences Unit (ECSU-Kolkata)


Mukherjee, Dipti Prasad (ECSU-Kolkata; ISI)

Abstract (Summary of the Work)

Active Contours, or snakes are used extensively for image segmentation and in related applications of image processing. In the present work we dis- cuss an active contour based image segmentation technique where points on the active contour are moved randomly following a stochastic scheme (Sto- chastic Active Contour). The evolution of active contour in an image is guided by an energy function. In this work, we derive an energy function suited for random movement of active contour points. Further the energy function is minimized using simulated annealing approach. The methodol- ogy is tested for a number of synthetic and real images that demonstrates the efficacy of the proposed scheme. Further the approach is extended for open curve evolution after designing energy functions suitabie for the random moves of the points on the open curve. Open curve evolution has also shown promising results.


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Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.


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