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SUPER PIXEL EXTRACTION VIA CONVEXITY INDUCED BOUNDARY ADAPTATION

2013-07-19
Tasli, H. Emrah
Cigla, Cevahir
Gevers, Theo
Alatan, Abdullah Aydın
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Creative Commons License
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.
Convexity constraint, Image segmentation
https://hdl.handle.net/11511/53479
Department of Electrical and Electronics Engineering, Conference / Seminar
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