Image retrieval based on dominant texture features

被引:11
|
作者
Tsai, Tienwei [1 ]
Huang, Yo-Ping [1 ]
Chiang, Te-Wei [2 ]
机构
[1] Tatung Univ, Dept Comp Sci & Engn, Taipei, Taiwan
[2] Chihlee Inst Technol, Dept Informat Networking Technol, Taipei, Taiwan
关键词
content-based image retrieval; discrete cosine transform; texture feature;
D O I
10.1109/ISIE.2006.295635
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a novel technique that can be used for fast indexing and retrieval of images based on their dominant texture features. Unlike the existing techniques that use computationally intensive texture features for content-based image retrieval, our proposed features are only derived from the DCT coefficients transformed from the Y-component in YUV color space. The dominant texture feature vector is mainly formed with the fundamental properties of global textures. In addition, to employ the fuzzy cognition concepts, our experimental system allows users to easily adjust weights for each individual feature component. Experimental results show that the proposed feature vector is compact with good retrieval accuracy.
引用
收藏
页码:441 / +
页数:3
相关论文
共 50 条
  • [31] An Image Retrieval Algorithm Base on Texture Features
    Song, Linlin
    Wang, Qinghu
    Pei, Zhili
    [J]. MECHANICAL COMPONENTS AND CONTROL ENGINEERING III, 2014, 668-669 : 1041 - 1044
  • [32] Texture features for browsing and retrieval of image data
    Manjunath, BS
    Ma, WY
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1996, 18 (08) : 837 - 842
  • [33] Rotated complex wavelet based texture features for content based image retrieval
    Kokare, M
    Biswas, PK
    Chatterji, BN
    [J]. PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 1, 2004, : 652 - 655
  • [34] Color and Texture Features Extraction on Content-based Image Retrieval
    Putri, Rahmaniansyah Dwi
    Prabawa, Harsa Wara
    Wihardi, Yaya
    [J]. 2017 3RD INTERNATIONAL CONFERENCE ON SCIENCE IN INFORMATION TECHNOLOGY (ICSITECH), 2017, : 711 - 715
  • [35] A fast and efficient image retrieval system based on color and texture features
    Singh, Chandan
    Kaur, Kanwal Preet
    [J]. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2016, 41 : 225 - 238
  • [36] Content-based image retrieval by integrating color and texture features
    Wang, Xiang-Yang
    Zhang, Bei-Bei
    Yang, Hong-Ying
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2014, 68 (03) : 545 - 569
  • [37] A novel color image retrieval method based on texture and deep features
    Wei, Weiyi
    Wang, Wanru
    Yang, Yijing
    Wang, Yu
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2022, 81 (01) : 659 - 679
  • [38] Comparative Analysis of Color and Texture Features in Content Based Image Retrieval
    Kaur, Jaspreet
    [J]. PROCEEDINGS OF 4TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, COMPUTING AND CONTROL (ISPCC 2K17), 2017, : 597 - 602
  • [39] Hybrid Features of Tamura Texture and Shape-Based Image Retrieval
    Pal, Naresh
    Kilaru, Aravind
    Savaria, Yvon
    Lakhssassi, Ahmed
    [J]. RECENT FINDINGS IN INTELLIGENT COMPUTING TECHNIQUES, VOL 3, 2018, 709 : 587 - 597
  • [40] Content based image retrieval using interest points and texture features
    Wolf, C
    Jolion, JM
    Kropatsch, W
    Bischof, H
    [J]. 15TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 4, PROCEEDINGS: APPLICATIONS, ROBOTICS SYSTEMS AND ARCHITECTURES, 2000, : 234 - 237