Title :
Hybrid color space and Support vector machines for classification
Author :
Rami, H. ; Hamri, M. ; Masmoudi, Lh
Author_Institution :
Phys. Dept., Mohamed V Univ., Rabat, Morocco
Abstract :
In this study, segmentation of color image is performed by supervised classification method based on hybrid color space. We define a kind of color space by selecting a set of color components which can belong to any of the different classical color spaces. We propose to classify pixels represented in the hybrid color space which is specifically designed to yield the best discrimination between the pixel classes and support vector machines (SVM). The proposed approach has been successfully tested on real color images.
Keywords :
image classification; image colour analysis; image representation; image segmentation; learning (artificial intelligence); support vector machines; SVM; color image segmentation; hybrid color space; pixel representation; supervised classification method; support vector machine; Extraterrestrial measurements; Image analysis; Image color analysis; Image segmentation; Laboratories; Physics; Pixel; Support vector machine classification; Support vector machines; Testing; Cross Validation; Feature Selection; Hybrid Color Space; RGB Images; Segmentation; Support Vector Machine (SVM);
Conference_Titel :
Multimedia Computing and Systems, 2009. ICMCS '09. International Conference on
Conference_Location :
Ouarzazate
Print_ISBN :
978-1-4244-3756-6
Electronic_ISBN :
978-1-4244-3757-3
DOI :
10.1109/MMCS.2009.5256648
