Content Based Image Retrieval Systems

The introduction of network and development of multimedia technologies are becoming more popular and so the users are not satisfied with the traditional information retrieval techniques. So nowadays the content based image retrieval are becoming a source of exact and fast retrieval. In this paper the techniques of content based image retrieval are discussed, analysed and compared. It also introduces the feature like neuro fuzzy technique, color histogram, texture and edge density for accurate and effective Content Based Image Retrieval System.

[1]  Malay Kumar Kundu,et al.  Edge based features for content based image retrieval , 2003, Pattern Recognit..

[2]  Swarup Medasani,et al.  Content-based image retrieval based on a fuzzy approach , 2004, IEEE Transactions on Knowledge and Data Engineering.

[3]  Yixin Chen,et al.  A Region-Based Fuzzy Feature Matching Approach to Content-Based Image Retrieval , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Ling Guan,et al.  Content-based image retrieval via distributed databases , 2008, CIVR '08.

[5]  Mathias Lux,et al.  Img(Rummager): An Interactive Content Based Image Retrieval System , 2009, 2009 Second International Workshop on Similarity Search and Applications.

[6]  Chunguang Zhou,et al.  Image retrieval using multi-granularity color features , 2008, 2008 International Conference on Audio, Language and Image Processing.

[7]  Anca L. Ralescu,et al.  Fuzzy hamming distance in a content-based image retrieval system , 2004, 2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542).

[8]  Muhammad Ikram,et al.  Image Retrieval in Multimedia Databases: A Survey , 2009, 2009 Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing.

[9]  Alberto Del Bimbo,et al.  Retrieval by Shape Similarity with Perceptual Distance and Effective Indexing , 2000, IEEE Trans. Multim..

[10]  Hui Zhang,et al.  Localized Content-Based Image Retrieval , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Marcel Worring,et al.  Content-Based Image Retrieval at the End of the Early Years , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Tatik Maftukhah,et al.  Fuzzy Relevance Feedback in Image Retrieval for Color Feature Using Query Vector Modification Method , 2010, J. Adv. Comput. Intell. Intell. Informatics.

[13]  B. S. Adiga,et al.  A Universal Model for Content-Based Image Retrieval , 2008 .

[14]  Peter A. Beling,et al.  Localized Content Based Image Retrieval with Self-Taught Multiple Instance Learning , 2009, 2009 IEEE International Conference on Data Mining Workshops.

[15]  Nozha Boujemaa,et al.  Embedding fuzzy logic in content based image retrieval , 2000, PeachFuzz 2000. 19th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.00TH8500).

[16]  Yanchun Zhang,et al.  An overview of content-based image retrieval techniques , 2004, 18th International Conference on Advanced Information Networking and Applications, 2004. AINA 2004..

[17]  Christian Hartvedt,et al.  Using Context to Understand User Intentions in Image Retrieval , 2010, 2010 Second International Conferences on Advances in Multimedia.

[18]  Yiannis S. Boutalis,et al.  img(Anaktisi): A Web Content Based Image Retrieval System , 2009, 2009 Second International Workshop on Similarity Search and Applications.

[19]  Wang Xiaoling,et al.  Application of the fuzzy logic in content-based image retrieval , 2005 .

[20]  Giorgio Giacinto,et al.  A nearest-neighbor approach to relevance feedback in content based image retrieval , 2007, CIVR '07.

[21]  Serge J. Belongie,et al.  Region-based image querying , 1997, 1997 Proceedings IEEE Workshop on Content-Based Access of Image and Video Libraries.

[22]  Dina Q. Goldin,et al.  Generating fuzzy semantic metadata describing spatial relations from images using the R-histogram , 2004, Proceedings of the 2004 Joint ACM/IEEE Conference on Digital Libraries, 2004..

[23]  Xu Jinhua,et al.  The Related Techniques of Content-Based Image Retrieval , 2008, 2008 International Symposium on Computer Science and Computational Technology.

[24]  Jilin Li,et al.  Local patterns constrained image histograms for image retrieval , 2008, 2008 15th IEEE International Conference on Image Processing.

[25]  Deok-Hwan Kim,et al.  QCluster: relevance feedback using adaptive clustering for content-based image retrieval , 2003, SIGMOD '03.

[26]  Neamat El Gayar,et al.  A new approach in content-based image retrieval using fuzzy , 2009, Telecommun. Syst..

[27]  Video Retrieval ACM International Conference on Content-Based Image and Video Retrieval : CIVR 2008, Niagara Falls, Ontario, Canada, 7-9 July 2008 , 2008 .

[28]  Siddhivinayak Kulkarni,et al.  Natural Language based Fuzzy Queries and Fuzzy Mapping of Feature Database for Image Retrieval , 2010 .

[29]  P. Sharma,et al.  Content based image retrieval using a neuro-fuzzy technique , 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

[30]  Malay Kumar Kundu,et al.  Content based image retrieval with fuzzy geometrical features , 2003, The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ '03..

[31]  Bhavani M. Thuraisingham,et al.  Semantic Web for Content Based Video Retrieval , 2009, 2009 IEEE International Conference on Semantic Computing.