Colour object recognition combining motion descriptors, zernike moments and support vector machine

被引:0
|
作者
Smach, Fethi [1 ,2 ]
Lemaitre, Cedric [1 ]
Miteran, Johel [1 ]
Gauthier, Jean Paul [1 ]
Abid, Mohamed [2 ]
机构
[1] Univ Burgundy, LeSi, BP 47870, F-21078 Dijon, France
[2] Univ Sfax, CES Lab, Sfax, Tunisia
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Fourier descriptors have been used successfully in the past to grey-level images, rigid bodied object. Here we used Motion Descriptors (MD) introduced recently by Gauthier et al., combined with Zernike Moments (ZM), in order to perform a recognition task in colour images. The feature vector for the MD obtained for each object appears to be unique and can be used for shape recognition. The MD, alone or combined with ZM, are used as an input of a Support Vector Machine (SVM) based classifier. We illustrate results on three available datasets: ORL faces database, COIL-100, which consists of 3D objects and A R faces.
引用
收藏
页码:12 / +
页数:2
相关论文
共 50 条
  • [21] A hardware architecture for fast video object recognition using SVM and Zernike Moments
    Lemaitre, Cedric
    Miteran, Johel
    Aubreton, Olivier
    Mosqueron, Rorriuald
    EIGHT INTERNATIONAL CONFERENCE ON QUALITY CONTROL BY ARTIFICIAL VISION, 2007, 6356
  • [22] Improved illumination-invariant descriptors for robust colour object recognition
    O'Callaghan, RJ
    Bull, DR
    2002 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS I-IV, PROCEEDINGS, 2002, : 3393 - 3396
  • [23] Classification of damages in composite images using Zernike moments and support vector machines
    Fredo, A. R. Jac
    Abilash, R. S.
    Femi, R.
    Mythili, A.
    Kumar, C. Suresh
    COMPOSITES PART B-ENGINEERING, 2019, 168 : 77 - 86
  • [24] Recognition of Human Actions Using Motion Capture Data and Support Vector Machine
    Wang, Jung-Ying
    Lee, Hahn-Ming
    2009 WRI WORLD CONGRESS ON SOFTWARE ENGINEERING, VOL 1, PROCEEDINGS, 2009, : 234 - +
  • [25] Human Motion Sequence Recognition Based on Feature Selection and Support Vector Machine
    Yu Yunlei
    Wang Mei
    Lin Limeng
    Zhang Chen
    2019 3RD INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE APPLICATIONS AND TECHNOLOGIES (AIAAT 2019), 2019, 646
  • [26] Sign Language Recognition Using Leap Motion A Support Vector Machine Approach
    Quesada, Luis
    Lopez, Gustavo
    Guerrero, Luis A.
    UBIQUITOUS COMPUTING AND AMBIENT INTELLIGENCE: SENSING, PROCESSING, AND USING ENVIRONMENTAL INFORMATION, 2015, 9454 : 277 - 288
  • [27] Near infrared face recognition by combining Zernike moments and undecimated discrete wavelet transform
    Farokhi, Sajad
    Shamsuddin, Siti Mariyam
    Sheikh, U. U.
    Flusser, Jan
    Khansari, Mohammad
    Jafari-Khouzani, Kourosh
    DIGITAL SIGNAL PROCESSING, 2014, 31 : 13 - 27
  • [28] HOGHS and Zernike Moments Features-Based Motion-Blurred Object Tracking
    Guang-Long, Wang
    Jie, Tian
    Wen-Jie, Zhu
    Dan, Fang
    INTERNATIONAL JOURNAL OF HUMANOID ROBOTICS, 2019, 16 (01)
  • [29] Face Recognition with Support Vector Machine
    Zhang Jian
    INTERNATIONAL CONFERENCE ON GRAPHIC AND IMAGE PROCESSING (ICGIP 2012), 2013, 8768
  • [30] Face recognition with support vector machine
    Zhang, SY
    Qiao, H
    2003 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS, INTELLIGENT SYSTEMS AND SIGNAL PROCESSING, VOLS 1 AND 2, PROCEEDINGS, 2003, : 726 - 730