Hybrid Color Space and Support Vector Machines for Classification

被引：0

作者：

Rami, H. ^{[1
]}

Hamri, M. ^{[1
]}

Masmoudi, Lh. ^{[1
]}

机构：

[1] Mohamed V Univ, LETS Lab, Dept Phys, Fac Sci, Rabat, Morocco

来源：

2009 INTERNATIONAL CONFERENCE ON MULTIMEDIA COMPUTING AND SYSTEMS (ICMCS 2009) | 2009年

关键词：

RGB Images; Segmentation; Support Vector Machine (SVM); Feature Selection; Cross Validation; Hybrid Color Space; IMAGE SEGMENTATION;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：483 / 486

页数：4

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