Paper
14 February 2015 Improving color image segmentation by spatial-color pixel clustering
Henryk Palus, Mariusz Frackiewicz
Author Affiliations +
Proceedings Volume 9445, Seventh International Conference on Machine Vision (ICMV 2014); 94450L (2015) https://doi.org/10.1117/12.2180548
Event: Seventh International Conference on Machine Vision (ICMV 2014), 2014, Milan, Italy
Abstract
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.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Henryk Palus and Mariusz Frackiewicz "Improving color image segmentation by spatial-color pixel clustering", Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 94450L (14 February 2015); https://doi.org/10.1117/12.2180548
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Cited by 1 scholarly publication.
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KEYWORDS
Image segmentation

Color image segmentation

Image processing

Image quality

Machine vision

RGB color model

Spatial resolution

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