Convexity constrained efficient superpixel and supervoxel extraction
SIGNAL PROCESSING-IMAGE COMMUNICATION, cilt.33, ss.71-85, 2015 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 33
- Basım Tarihi: 2015
- Doi Numarası: 10.1016/j.image.2015.02.005
- Dergi Adı: SIGNAL PROCESSING-IMAGE COMMUNICATION
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Sayfa Sayıları: ss.71-85
- Anahtar Kelimeler: Superpixel, Segmentation, Geometry constrain, Supervoxel
- Orta Doğu Teknik Üniversitesi Adresli: Evet
Özet
This paper presents an efficient superpixel (SP) and supervoxel (SV) extraction method that aims improvements over the state-of-the-art in terms of both accuracy and computational complexity. Segmentation performance is improved through convexity constrained distance utilization, whereas computational efficiency is achieved by replacing complete region processing by a boundary adaptation technique. Starting from the uniformly distributed, rectangular (cubical) equal size (volume) superpixels (supervoxels), region boundaries are iteratively adapted towards object edges. Adaptation is performed by assigning the boundary pixels to the most similar neighboring SPs (SVs). At each iteration, SP (SV) regions are updated; hence, progressively converging to compact pixel groups. Detailed experimental comparisons against the state-of-the-art competing methods validate the performance of the proposed technique considering both accuracy and speed. (C) 2015 Elsevier B.V. All rights reserved.