Orientation code matching for robust object search

被引:0
|
作者
Ullah, F [1 ]
Kaneko, S [1 ]
Igarashi, S [1 ]
机构
[1] Hokkaido Univ, Sapporo, Hokkaido 0608628, Japan
关键词
object search; matching; robustness; orientation code; object tracking;
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
A new method for object search is proposed. Conventional template matching schemes tend to fail in presence of irregularities and ill-conditions like background variations, illumination fluctuations resulting from shadowing or highlighting etc. The proposed scheme is robust against such irregularities in the real world scenes since it is based on matching gradient information around each pixel, computed in the form of orientation codes, rather than the gray levels directly. A probabilistic model for robust matching is given and verified by real image data. Experimental results for real world scenes demonstrate the effectiveness of the proposed method for object search in the presence of different potential causes of mismatches.
引用
收藏
页码:999 / 1006
页数:8
相关论文
共 50 条
  • [21] Palmprint verification based on robust line orientation code
    Jia, Wei
    Huang, De-Shuang
    Zhang, David
    PATTERN RECOGNITION, 2008, 41 (05) : 1504 - 1513
  • [22] A Robust Fingerprint Matching System Using Orientation Features
    Kumar, Ravinder
    Chandra, Pravin
    Hanmandlu, Madasu
    JOURNAL OF INFORMATION PROCESSING SYSTEMS, 2016, 12 (01): : 83 - 99
  • [23] Sequential binary code selection for robust object tracking
    Xin Guo
    Ning Xiao
    Likun Zhang
    Multimedia Tools and Applications, 2020, 79 : 6951 - 6963
  • [24] Object recognition by partial shape matching guided search
    Saber, E
    Xu, YW
    Tekalp, AM
    2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1-5: SPEECH PROCESSING, 2005, : 145 - 148
  • [25] Robust Object Tracking with Compressive Sensing and Patches Matching
    Pi, Jiatian
    Hu, Keli
    Zhang, Xiaolin
    Gu, Yuzhang
    Zhan, Yunlong
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2016, E99D (06): : 1720 - 1723
  • [26] Segmentation and Matching: Towards a Robust Object Detection System
    Huang, Jing
    You, Suya
    2014 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV), 2014, : 325 - 332
  • [27] Robust object matching for persistent tracking with heterogeneous features
    Guo, Yanlin
    Hsu, Steve
    Sawhney, Harpreet S.
    Kumar, Rakesh
    Shan, Ying
    IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2007, 29 (05) : 824 - 839
  • [28] Realtime and robust object matching with a large number of templates
    Chaoqun Hong
    Jianke Zhu
    Jun Yu
    Jun Cheng
    Xuhui Chen
    Multimedia Tools and Applications, 2016, 75 : 1459 - 1480
  • [29] Sequential binary code selection for robust object tracking
    Guo, Xin
    Xiao, Ning
    Zhang, Likun
    MULTIMEDIA TOOLS AND APPLICATIONS, 2020, 79 (11-12) : 6951 - 6963
  • [30] Object Matching Using Speeded Up Robust Features
    Verma, Nishchal Kumar
    Goyal, Ankit
    Vardhan, A. Harsha
    Sevakula, Rahul Kumar
    Salour, Al
    INTELLIGENT AND EVOLUTIONARY SYSTEMS, IES 2015, 2016, 5 : 415 - 427