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Nature of Computation and Communication. International Conference, ICTCC 2014, Ho Chi Minh City, Vietnam, November 24-25, 2014, Revised Selected Papers

Research Article

Object Classification Based on Contourlet Transform in Outdoor Environment

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  • @INPROCEEDINGS{10.1007/978-3-319-15392-6_32,
        author={Nguyen Binh},
        title={Object Classification Based on Contourlet Transform in Outdoor Environment},
        proceedings={Nature of Computation and Communication. International Conference, ICTCC 2014, Ho Chi Minh City, Vietnam, November 24-25, 2014, Revised Selected Papers},
        proceedings_a={ICTCC},
        year={2015},
        month={2},
        keywords={Object classification Contourlet transform Support vector machine},
        doi={10.1007/978-3-319-15392-6_32}
    }
    
  • Nguyen Binh
    Year: 2015
    Object Classification Based on Contourlet Transform in Outdoor Environment
    ICTCC
    ICST
    DOI: 10.1007/978-3-319-15392-6_32
Nguyen Binh1,*
  • 1: Ho Chi Minh City University of Technology
*Contact email: ntbinh@cse.hcmut.edu.vn

Abstract

Classification of objects is an important task in computer vision. In the case that the objects are occlusion or outdoor environment, classification of objects is a challenging problem. The primary goal of this paper is to classify the object into two classes: human and car in an outdoor environment. In order to detect object classification, most of existing methods separated detecting object region from pre-defined background model. Here, we propose a method to implement classification of human and car in outdoor environment using contourlet transform combined with support vector machine as a classifier for classification of objects. The proposed method tested on standard dataset like PEST2001 dataset. For demonstrating the superiority of the proposed method, we have compared the results with the other recent methods available in literature.

Keywords
Object classification Contourlet transform Support vector machine
Published
2015-02-05
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-319-15392-6_32
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