The JPEG image query feedback research based on the Compressed domain

被引:0
|
作者
Wang, Jianfeng [1 ]
Liu, Zikun [1 ]
Li, Mingke [1 ]
Wu, Wenming [1 ]
Zhao, Xiaorong [1 ]
机构
[1] ChongQing Aerosp Polytech, Chongqing 400021, Peoples R China
来源
PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON MECHATRONICS AND INDUSTRIAL INFORMATICS | 2015年 / 31卷
关键词
DCT; CBIR; Compressed domain; Feedback;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The research focus of the CBIR is to improving the accuracy of the image retrieval with the feedback technology. But this technology can not solve the problem between the low-level feature and high-level semantic, which is the difficulty of the CBIR and the difficulty of the image compressing and video retrieval. This paper shows the basic method of image retrieval in the compressed domain and the developing situation of the feedback. One complicated feedback framework at the CBIR are proposed.
引用
收藏
页码:819 / 823
页数:5
相关论文
共 50 条
  • [31] Image Segmentation with Multi-feature Fusion in Compressed Domain based on Region-Based Graph
    Luo, Hong-Chuan
    Sun, Bo
    Zhou, Hang-Kai
    Cao, Wen-Sen
    INTERNATIONAL ARAB JOURNAL OF INFORMATION TECHNOLOGY, 2023, 20 (02) : 159 - 169
  • [32] Data-driven Sparsity-based Restoration of JPEG-compressed Images in Dual Transform-Pixel Domain
    Liu, Xianming
    Wu, Xiaolin
    Zhou, Jiantao
    Zhao, Debin
    2015 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2015, : 5171 - 5178
  • [33] Factor Histogram based Forgery Localization in Double Compressed JPEG Images
    Mire, Archana V.
    Dhok, S. B.
    Mistry, N. J.
    Porey, P. D.
    ELEVENTH INTERNATIONAL CONFERENCE ON COMMUNICATION NETWORKS, ICCN 2015/INDIA ELEVENTH INTERNATIONAL CONFERENCE ON DATA MINING AND WAREHOUSING, ICDMW 2015/NDIA ELEVENTH INTERNATIONAL CONFERENCE ON IMAGE AND SIGNAL PROCESSING, ICISP 2015, 2015, 54 : 690 - 696
  • [34] Fuzzy Relevance Feedback in Image Retrieval for Color Feature Using Query Vector Modification Method
    Widyanto, M. Rahmat
    Maftukhah, Tatik
    JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS, 2010, 14 (01) : 34 - 38
  • [35] Visual Morphing Based on the Compressed Domain
    Jiang, Yiwei
    Xu, De
    Liu, Na
    Lang, Congyan
    JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, 2010, 26 (06) : 2075 - 2091
  • [36] Fuzzy intensification operator based contrast enhancement in the compressed domain
    Florea, Camelia
    Vlaicu, Aurel
    Gordan, Mihaela
    Orza, Bogdan
    APPLIED SOFT COMPUTING, 2009, 9 (03) : 1139 - 1148
  • [37] Pornographic Image Recognition in Compressed Domain Based on Multi-Cost Sensitive Decision Tree
    Zhao Shiwei
    Zhuo Li
    Wang Suyu
    Li Xiaoguang
    Shen Lansun
    ICCSIT 2010 - 3RD IEEE INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY, VOL 4, 2010, : 225 - 229
  • [38] Region-based image retrieval in the compressed domain using shape-adaptive DCT
    Amina Belalia
    Kamel Belloulata
    Kidiyo Kpalma
    Multimedia Tools and Applications, 2016, 75 : 10175 - 10199
  • [39] Region-based image retrieval in the compressed domain using shape-adaptive DCT
    Belalia, Amina
    Belloulata, Kamel
    Kpalma, Kidiyo
    MULTIMEDIA TOOLS AND APPLICATIONS, 2016, 75 (17) : 10175 - 10199
  • [40] A review on document image analysis techniques directly in the compressed domain
    Mohammed Javed
    P. Nagabhushan
    Bidyut B. Chaudhuri
    Artificial Intelligence Review, 2018, 50 : 539 - 568