Image Retrieval by Shape and Color Contents and Relevance Feedback

被引:1
作者
Yasmin, Mussarat [1 ]
Mohsin, Sajjad [1 ]
机构
[1] Comsats Inst Informat Technol, Dept Comp Sci, Wah Cantt, Pakistan
来源
10TH INTERNATIONAL CONFERENCE ON FRONTIERS OF INFORMATION TECHNOLOGY (FIT 2012) | 2012年
关键词
content based search; image retrieval; shape; relevance feedback; CBIR;
D O I
10.1109/FIT.2012.57
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the current era of digital communication, the use of digital images has grown high for expressing, sharing and interpreting information. While working with the digital images it is quite often that one needs to search for a specific image for a particular situation based on the visual contents of the image. Image retrieval by contents is one of the modern ways for searching huge digital image repositories for specific images. With the growing usage of World Wide Web CBIR is now very commonly used on most of the websites, software and database systems. In past years much of the research has been conducted in this domain and many CBIR systems have been proposed, implemented and being used. Different CBIR systems have different approaches to find images based on their contents and thus they have different performance and accuracy measures. There are some really smart techniques proposed by researchers for efficient and robust content based image retrieval. In this research, the aim is to highlight the efforts of researchers who conducted some brilliant work, based on this knowledge I will propose new combinational techniques for Content Based Image Retrieval focusing high performance and improved relevance and will provide proof of concept for intelligent content based image retrieval.
引用
收藏
页码:282 / 287
页数:6
相关论文
共 43 条
[1]  
Adnan A, 2007, THIRD INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES 2007, PROCEEDINGS, P222
[2]  
Afifi Ahmed J., 2011, IMAGE RETRIEVAL BASE
[3]  
[Anonymous], IEEE RIVF INT C COMP
[4]   A fast compression-based similarity measure with applications to content-based image retrieval [J].
Cerra, Daniele ;
Datcu, Mihai .
JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2012, 23 (02) :293-302
[5]  
Chen Hongjun, 2011, 2011 International Conference on Consumer Electronics, Communications and Networks (CECNet), P4858, DOI 10.1109/CECNET.2011.5768214
[6]   Object Segmentation of Database Images by Dual Multiscale Morphological Reconstructions and Retrieval Applications [J].
Chen, Jiann-Jone ;
Su, Chun-Rong ;
Grimson, W. Eric L. ;
Liu, Jun-Lin ;
Shiue, De-Hui .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2012, 21 (02) :828-843
[7]  
Chen Xin-Wu, 2010, ED INF TECHN ICEIT 2, V1
[8]  
Chen Xinwu, 2010, COMP APPL SYST MOD I, V9
[9]  
Chin-Chen Chang, 2008, 2008 Second International Conference on Future Generation Communication and Networking Symposia (FGCNS), P181, DOI 10.1109/FGCNS.2008.32
[10]   A comparison of relevance feedback strategies in CBIR [J].
Das, Gita ;
Ray, Sid .
6TH IEEE/ACIS INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION SCIENCE, PROCEEDINGS, 2007, :100-+