Content Based Image Retrieval by Using an Integrated Matching Technique Based on Most Similar Highest Priority Principle on the Color and Texture Features of the Image Sub-blocks

被引:0
作者
Kavitha, Ch. [1 ]
Rao, M. Babu [2 ]
Rao, B. Prabhakara [3 ]
Govardhan, A. [4 ]
机构
[1] Gudlavalleru Engn Coll, IT Dept, Gudlavalleru, Andhra Pradesh, India
[2] Gudlavalleru Engn Coll, CSE Dept, Gudlavalleru, Andhra Pradesh, India
[3] JNTUK, Kakinada, AP, India
[4] JNTUH Coll Engn, Jagtial, AP, India
来源
INFORMATION TECHNOLOGY AND MOBILE COMMUNICATION | 2011年 / 147卷
关键词
Image retrieval; color; texture; GLCM; integrated matching;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we propose an efficient technique for content based image retrieval which uses the local color and texture features of the image. Firstly the image is divided into sub blocks of equal size. The color and texture features of each sub-block are computed. Color of each sub-block is extracted by quantifying the HSV color space into non-equal intervals and the color feature is represented by cumulative histogram. Texture of each sub-block is obtained by using gray level co-occurrence matrix. An integrated matching scheme based on Most Similar Highest Priority principle is used to compare the query and target image. The adjacency matrix of a bipartite graph is formed using the sub-blocks of query and target image. This matrix is used for matching the images. Euclidean distance is used in retrieving the similar images. The efficiency of the method is demonstrated with the results.
引用
收藏
页码:399 / +
页数:2
相关论文
共 50 条
[31]   On Comparative Performance Analysis of Color, Edge and Texture based Histograms for Content Based Color Image Retrieval [J].
Kaur, Kanwal Preet .
2014 3RD INTERNATIONAL CONFERENCE ON RELIABILITY, INFOCOM TECHNOLOGIES AND OPTIMIZATION (ICRITO) (TRENDS AND FUTURE DIRECTIONS), 2014,
[32]   Fractal-based Texture and HSV Color Features for Fabric Image Retrieval [J].
Suciati, Nanik ;
Herumurti, Darlis ;
Wijaya, Arya Yudhi .
PROCEEDINGS 5TH IEEE INTERNATIONAL CONFERENCE ON CONTROL SYSTEM, COMPUTING AND ENGINEERING (ICCSCE 2015), 2015, :178-182
[33]   Content Based Image Retrieval using Local and Global features descriptor [J].
Kabbai, Leila ;
Abdellaoui, Mehrez ;
Douik, Ali .
2016 2ND INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES FOR SIGNAL AND IMAGE PROCESSING (ATSIP), 2016, :151-154
[34]   Content-based image retrieval using color histogram [J].
Huang, Wen-Bei ;
He, Liang ;
Gu, Jun-Zhong .
Journal of Donghua University (English Edition), 2006, 23 (04) :98-102
[35]   Fast Content Based Color Image Retrieval System Based on Texture Analysis of Edge Map [J].
Salehian, Hesamoddin ;
Zamani, Fatemeh ;
Jamzad, Mansour .
MATERIAL AND MANUFACTURING TECHNOLOGY II, PTS 1 AND 2, 2012, 341-342 :168-172
[36]   Image Retrieval System based on Color Global and Local Features Combined with GLCM for Texture Features [J].
Alnihoud, Jehad Q. .
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2018, 9 (09) :164-171
[37]   Content-based image retrieval using multiple features [J].
Zhang, Chi ;
Huang, Lei .
Journal of Computing and Information Technology, 2014, 22 (SpecialIssue) :1-10
[38]   Generic and fully automatic content-based image retrieval using color [J].
Choubey, SK ;
Raghavan, VV .
PATTERN RECOGNITION LETTERS, 1997, 18 (11-13) :1233-1240
[39]   Content Based Image Retrieval using Gabor Filters and Color Coherence Vector [J].
Singh, Jyotsna ;
Bajaj, Ahsaas ;
Mittal, Anirudh ;
Khanna, Ansh ;
Karwayun, Rishabh .
PROCEEDINGS OF THE 2018 IEEE 8TH INTERNATIONAL ADVANCE COMPUTING CONFERENCE (IACC 2018), 2018, :290-295
[40]   Content-Based Image Retrieval Using Texture Structure Histogram [J].
Hou, Gang ;
Feng, Qinghe ;
Zhang, Xiaoxue ;
Kong, Jun ;
Zhang, Ming .
PROCEEDINGS OF 3RD INTERNATIONAL CONFERENCE ON MULTIMEDIA TECHNOLOGY (ICMT-13), 2013, 84 :1356-1363