RESEARCH ON IMAGE RETRIEVAL TECHNOLOGY BASED ON IMAGE FINGERPRINT AND COLOR FEATURES

被引：0
|
作者：
Wang, Yaguang [1 ]
Sui, Aina [1 ]
Fu, Wenlong [2 ]
机构：
[1] Commun Univ China, Sch Comp, Beijing, Peoples R China
[2] Commun Univ China, Neurosci & Intelligent Media Inst, Beijing, Peoples R China
来源：
PROCEEDINGS OF 2016 INTERNATIONAL CONFERENCE ON AUDIO, LANGUAGE AND IMAGE PROCESSING (ICALIP) | 2016年
关键词：
Image fingerprint; Perceptual hash; Color histogram; Similarity; Precision;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Content based video retrieval and content-based image retrieval are the hot research topics in recent years. Image feature extraction has played a very important role in the retrieval process. In this paper, we use the image color features and the image fingerprint extracted by the improved perceptual hash algorithm. In order to combine these two features, we have done a lot of tests to find the optimal weight values. We used these to have image retrieval experiments on Corel set and analyzed the results. Experiments show that the improved algorithm has higher retrieval efficiency and the precision of retrieval result is improved.
引用
收藏
页码：447 / 451
页数：5
相关论文
共 50 条
  • [31] Color and Texture Features for Image Indexing and Retrieval
    Murala, Subrahmanyam
    Balaji, Anil
    Maheshwari, Gonde R. P.
    [J]. 2009 IEEE INTERNATIONAL ADVANCE COMPUTING CONFERENCE, VOLS 1-3, 2009, : 1411 - 1416
  • [32] Combining Color and Shape Features for Image Retrieval
    Lee, XiaoFu
    Yin, Qian
    [J]. UNIVERSAL ACCESS IN HUMAN-COMPUTER INTERACTION: APPLICATIONS AND SERVICES, PT III, 2009, 5616 : 569 - 576
  • [33] Color Features Performance Comparison for Image Retrieval
    Borghesani, Daniele
    Grana, Costantino
    Cucchiara, Rita
    [J]. IMAGE ANALYSIS AND PROCESSING - ICIAP 2009, PROCEEDINGS, 2009, 5716 : 902 - 910
  • [34] Combining color and texture features for image retrieval
    Wang, Guiting
    Tian, Baobao
    Jiao, Licheng
    [J]. MIPPR 2007: AUTOMATIC TARGET RECOGNITION AND IMAGE ANALYSIS; AND MULTISPECTRAL IMAGE ACQUISITION, PTS 1 AND 2, 2007, 6786
  • [35] Distributed Image Retrieval with Color and Keypoint Features
    Lagiewka, Michal
    Korytkowski, Marcin
    Scherer, Rafal
    [J]. 2017 IEEE INTERNATIONAL CONFERENCE ON INNOVATIONS IN INTELLIGENT SYSTEMS AND APPLICATIONS (INISTA), 2017, : 45 - 50
  • [36] Heuristic features for color correlogram for image retrieval
    Park, Jongan
    Han, Seungjo
    An, Youngeun
    [J]. INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCES AND ITS APPLICATIONS, PROCEEDINGS, 2008, : 9 - 13
  • [37] Image retrieval using local color features
    Wu, TC
    Leou, JJ
    Kang, LW
    [J]. ICCE: 2005 INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS, DIGEST OF TECHNICAL PAPERS, 2005, : 55 - 56
  • [38] Research and implementation of retrieval technology based on image content
    Wang, J. X.
    Wang, Y. L.
    Sun, H. Y.
    [J]. Manufacturing and Engineering Technology, 2015, : 357 - 360
  • [39] REGION BASED LOCALIZED MATCHING IMAGE RETRIEVAL SYSTEM USING COLOR-SIZE FEATURES FOR IMAGE RETRIEVAL
    Memon, Muhammad Hammad
    Li, Jianping
    Memon, Imran
    Arain, Qasim Ali
    Memon, Muhammad Hunain
    [J]. 2017 14TH INTERNATIONAL COMPUTER CONFERENCE ON WAVELET ACTIVE MEDIA TECHNOLOGY AND INFORMATION PROCESSING (ICCWAMTIP), 2017, : 211 - 215
  • [40] Research on Algorithm of Image Segmentation Based on Color Features
    Bai, Jie-yun
    Ren, Hong-e
    [J]. ADVANCED RESEARCH ON COMPUTER SCIENCE AND INFORMATION ENGINEERING, PT I, 2011, 152 : 73 - 78
12345