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
收藏
页码：483 / 486
页数：4
相关论文
共 50 条
  • [1] Color Image Classification Using Support Vector Machines
    冯霞
    中国民航学院学报, 2003, (S2) : 184 - 190
  • [2] Classification in a normalized feature space using support vector machines
    Graf, ABA
    Smola, AJ
    Borer, S
    IEEE TRANSACTIONS ON NEURAL NETWORKS, 2003, 14 (03): : 597 - 605
  • [3] Hybrid classification algorithms based on boosting and support vector machines
    Maia, Thiago Turchetti
    Braga, Antonio Padua
    de Carvalho, Andre F.
    KYBERNETES, 2008, 37 (9-10) : 1469 - 1491
  • [4] Color Deconvolution and Support Vector Machines
    Berger, Charles E. H.
    Veenman, Cor J.
    COMPUTATIONAL FORENSICS, PROCEEDINGS, 2009, 5718 : 174 - 180
  • [5] Classification of Imbalanced Data by Oversampling in Kernel Space of Support Vector Machines
    Mathew, Josey
    Pang, Chee Khiang
    Luo, Ming
    Leong, Weng Hoe
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 29 (09) : 4065 - 4076
  • [6] A hybrid approach to error reduction of support vector machines in document classification
    Tae, Yoon-Shik
    Son, Jeong woo
    Kong, Mi-hwa
    Lee, Jun-Seok
    Park, Seong-Bae
    Lee, Sang-Jo
    THIRD INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY: NEW GENERATIONS, PROCEEDINGS, 2006, : 501 - +
  • [7] Hybrid huberized support vector machines for microarray classification and gene selection
    Wang, Li
    Zhu, Ji
    Zou, Hui
    BIOINFORMATICS, 2008, 24 (03) : 412 - 419
  • [8] Support vector machines for texture classification
    Kim, KI
    Jung, K
    Park, SH
    Kim, HJ
    IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2002, 24 (11) : 1542 - 1550
  • [9] Clifford support vector machines for classification
    Bayro-Corrochano, E
    Arana-Daniel, N
    Vallejo-Gutiérres, JR
    ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING - ICAISC 2004, 2004, 3070 : 9 - 16
  • [10] Multicategory Classification by Support Vector Machines
    Erin J. Bredensteiner
    Kristin P. Bennett
    Computational Optimization and Applications, 1999, 12 : 53 - 79
12345