SUPER PIXEL EXTRACTION VIA CONVEXITY INDUCED BOUNDARY ADAPTATION

Date

2013-07-19

Author

Tasli, H. Emrah
Cigla, Cevahir
Gevers, Theo
Alatan, Abdullah Aydın

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

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This study presents an efficient super-pixel extraction algorithm with major contributions to the state-of-the-art in terms of accuracy and computational complexity. Segmentation accuracy is improved through convexity constrained geodesic distance utilization; while computational efficiency is achieved by replacing complete region processing with boundary adaptation idea. Starting from the uniformly distributed rectangular equal-sized super-pixels, region boundaries are adapted to intensity edges iteratively by assigning boundary pixels to the most similar neighboring super-pixels. At each iteration, super-pixel regions are updated and hence progressively converging to compact pixel groups. Experimental results with state-of-the-art comparisons, validate the performance of the proposed technique in terms of both accuracy and speed.

Subject Keywords

Convexity constraint, Image segmentation

URI

https://hdl.handle.net/11511/53479

Conference Name

IEEE International Conference on Multimedia and Expo Workshops (ICMEW)

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

H. E. Tasli, C. Cigla, T. Gevers, and A. A. Alatan, “SUPER PIXEL EXTRACTION VIA CONVEXITY INDUCED BOUNDARY ADAPTATION,” presented at the IEEE International Conference on Multimedia and Expo Workshops (ICMEW), San Jose, CA, 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53479.