Image segmentation is one of the most difficult steps in the computer vision process. Pixel clustering is only one among many techniques used in image segmentation. In this paper is proposed a new segmentation technique, making clustering in the five-dimensional feature space built from three color components and two spatial coordinates. The advantages of taking into account the information about the image structure in pixel clustering are shown. The proposed 5D k-means technique requires, similarly to other segmentation techniques, an additional postprocessing to eliminate oversegmentation. Our approach is evaluated on different simple and complex images.

Date Published: 14 February 2015
PDF: 5 pages
Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 94450L (14 February 2015); doi: 10.1117/12.2180548

Published in SPIE Proceedings Vol. 9445:
Seventh International Conference on Machine Vision (ICMV 2014)
Antanas Verikas; Branislav Vuksanovic; Petia Radeva; Jianhong Zhou, Editor(s)