CBIR based on color and low-level texture features

被引：0
|
作者：
Choras, Ryszard S. [1 ]
机构：
[1] Univ Technol & LS, Fac Telecommun & Elect Engn, PL-85791 Bydgoszcz, Poland
来源：
PROCEEDINGS OF THE FOURTH IASTED INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, PATTERN RECOGNITION, AND APPLICATIONS | 2007年
关键词：
CBIR; color histogram; Gabor filters; similarity metrics; texture features;
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：
Content-based image retrieval systems allow the user to interactively search image databases looking for those images which are similar to a specified query image. Similarity between images is then assessed by computing similarity between feature vectors. These features are represented in the vector form, and often are combined together. This paper explores image retrieval mechanisms based on a combination of texture and color features. Texture features are extracted using the Gabor filters analysis. Color moments are used as color features.
引用
收藏
页码：259 / 263
页数：5
相关论文
共 50 条
  • [21] LOW-LEVEL VISUAL PROCESSES AND TEXTURE SEGREGATION
    GRAHAM, N
    PHYSICA SCRIPTA, 1989, 39 (01) : 147 - 152
  • [22] Based on the Semantics of the Low-level Visual Features Image Retrieval
    Zeng, Xianwen
    Shen, Xuedong
    ADVANCED COMPOSITE MATERIALS, PTS 1-3, 2012, 482-484 : 512 - 517
  • [23] Image similarity measure based on low-level visual features
    Weidianzixue yu Jisuanji, 6 (28-32):
  • [24] Film classification based on low-level visual effect features
    Huang, Hui-Yu
    Shih, Weir-Sheng
    Hsu, Wen-Hsing
    JOURNAL OF ELECTRONIC IMAGING, 2008, 17 (02)
  • [25] Movie Posters Classification into Genres Based on Low-level Features
    Ivasic-Kos, Marina
    Pobar, Miran
    Mikec, Luka
    2014 37TH INTERNATIONAL CONVENTION ON INFORMATION AND COMMUNICATION TECHNOLOGY, ELECTRONICS AND MICROELECTRONICS (MIPRO), 2014, : 1198 - 1203
  • [26] Low-Level Features for Paraphrase Identification
    Pronoza, Ekaterina
    Yagunova, Elena
    ADVANCES IN ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, MICAI 2015, PT I, 2015, 9413 : 59 - 71
  • [27] A novel approach of color-texture based CBIR using Fuzzy logic
    Department of CSE/IT, Madhav Institute of Technology and Science, Gwalior, M.P., India
    Int. J. Database Theory Appl., 4 (79-86):
  • [28] Shape, Color and Texture Based CBIR System Using Fuzzy Logic Classifier
    Yuvaraj, D.
    Sivaram, M.
    Karthikeyan, B.
    Abdulazeez, Jihan
    CMC-COMPUTERS MATERIALS & CONTINUA, 2019, 59 (03): : 729 - 739
  • [29] Color constancy: The role of low-level mechanisms
    Spitzer, H
    Rosenbluth, A
    SPATIAL VISION, 2002, 15 (03): : 277 - 302
  • [30] A CBIR system based on saliency driven local image features and multi orientation texture features
    Pradhan, Jitesh
    Pal, Arup Kumar
    Banka, Haider
    JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2022, 83
12345