A Simple Algorithm of Superpixel Segmentation With Boundary Constraint

• Published in: IEEE transactions on circuits and systems for video technology Vol. 27; no. 7; pp. 1502 - 1514
• Main Authors: Zhang, Yongxia, Li, Xuemei, Gao, Xifeng, Zhang, Caiming
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adhesion; Algorithm design and analysis; Clustering algorithms; Complexity theory; Computer vision; Distance measurement; Image edge detection; Image preprocessing; Image segmentation; oversegmentation; Seeds; Shape; superpixel
• ISSN: 1051-8215; 1558-2205
• DOI: 10.1109/TCSVT.2016.2539839

As one of the most popular image oversegmentations, superpixel has been commonly used as supporting regions for primitives to reduce computations in various computer vision tasks. In this paper, we propose a novel superpixel segmentation approach based on a distance function that is designed to balance among boundary adherence, intensity homogeneity, and compactness (COM) characteristics of the resulting superpixels. Given an expected number of superpixels, our method begins with initializing the superpixel seed positions to obtain the initial labels of pixels. Then, we optimize the superpixels iteratively based on the defined distance measurement. We update the positions and intensities of superpixel seeds based on the three-sigma rule. The experimental results demonstrate that our algorithm is more effective and accurate than previous superpixel methods and achieves a comparable tradeoff between superpixel COM and adherence to object boundaries.