Color Reduction Using the Combination of the Kohonen Self-Organized Feature Map and the Gustafson-Kessel Fuzzy Algorithm

The color reduction in digital images is an active research area in digital image processing. In many applications such as image segmentation, analysis, compression and transmission, it is preferable to have images with a limited number of colors. In this paper, a color clustering technique which is a combination of a Kohonen Self Organized Featured Map (KSOFM) and a fuzzy clustering algorithm is proposed. Initially, we reduce the number of image’s colors by using a KSOFM. Then, using the KSOFM color clustering results as starting values, we obtain the final colors by a Gustafson-Kessel Fuzzy Classifier (GKFC). Doing this, we lead to better color classification results because the final color classes obtained are not spherical.

• Type: Conference
• Year: 2007
• Where: MLDM
• Authors: Konstantinos Zagoris, Nikos Papamarkos, Ioannis Koustoudis
• Keywords: Color, Color Clustering Technique, Fuzzy Clustering Algorithm, Machine Learning, MLDM 2007