Topics: Color, Cluster analysis, Image processing Pages: 21 (6085 words) Published: March 14, 2013

Color Space Analysis for Color Image Segmentation of Natural Scenes by K-means Based Clustering Jia Song(1,∗) , Eva M. Valero(1) , Juan L. Nieves(1)
1. Optics Department, Faculty of Science, University of Granada, Spain (∗)

Corresponding author Email:
Recibido / Received: dd/mm/yyyy Aceptado / Accepted: dd/mm/yyyy

ABSTRACT: In this paper, we propose to segment color images of natural scenes by pixel clustering in different color spaces in order to compare the performances of the color spaces. Eight color spaces are evaluated, including perceptual and non-perceptual color spaces. The clustering methods applied in this work are k-means and its extensions. Segmentation results are evaluated by calculating the degree of matching with the benchmark created by manual labeling, and visual evaluation is also applied as a reference. A series of experiments were designed and conducted. Results show that the performances of the color spaces are dependent on the scenes, and it is possible to choose a proper color space manually for a specific image scene segmentation task according to the data dependency patterns analyzed from the experiment results. Key words: color image segmentation, natural scenes, color spaces, k-means clustering

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Opt. Pura Apl. NN (A) XXX-XXX (YYYY)


c Sociedad Española de Óptica


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