Content Based Image Retrieval using Color and Texture Content

International Journal of Computer Trends and Technology (IJCTT)          
© 2017 by IJCTT Journal
Volume-48 Number-2
Year of Publication : 2017
Authors : Suresh M B, Dr.B Mohankumar Naik
DOI :  10.14445/22312803/IJCTT-V48P117


Suresh M B, Dr.B Mohankumar Naik "Content Based Image Retrieval using Color and Texture Content". International Journal of Computer Trends and Technology (IJCTT) V48(2):78-84, June 2017. ISSN:2231-2803. Published by Seventh Sense Research Group.

Abstract -
This paper describes a hybrid feature extraction approach of our research and solution to the problem of designing a CBIR system manually. Two features are used for retrieving the images such as color and texture. Color feature is extracted by using different color space such as RGB, HSV and YCbCr. Texture feature is extracted by applying Gray Level Co-occurrence Matrix (GLCM). The image is retrieved by combining color and texture feature and the color space which gives the best result as analyzed using precision and recall graph.

[1] B. Szant´o, P. Pozsegovics, Z. V´amossy, Sz. Sergy´an, “Sketch4Match – Content-based Image Retrieval System Using Sketches”, 978-1-4244- 7430-1/11/$26.00 ©2011 IEEE.
[2] Hatice Cinar Akakin and Metin N. Gurcan, “Content Based Microscopic Image Retrieval System for Multi-Image Queries”, IEEE Transactions On Information Technology In Biomedicine, VOL. 16, NO. 4, JULY 2012.
[3] Yong-Hwan Lee and Sang-Burm Rhee, Bonam Kim, “Content-based Image Retrieval Using Wavelet Spatial-Color and Gabor Normalized Texture in Multi-resolution Database”, 978-0- 7695- 4684-1/12 $26.00 © 2012 IEEE, DOI 10.1109/IMIS.2012.98.
[4] M. Singha K. Hemachandran1 A. Paul, “Content-based image retrieval using the combination of the fast wavelet transformation and the color histogram”, IET Image Process., 2012, Vol. 6, Iss. 9, pp. 1221–1226 1221; do: 10.1049/iet- ipr.2011.0453.
[5] S. Mangijao Singh , K. Hemachandran , “Content-Based Image Retrieval using Color Moment and Gabor Texture Feature”, IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 5, No 1, September 2012; ISSN (Online): 1694- 0814.
[6] Jean-Francois Omhover, Marcin Detyniecki,University P. et M. Curie – CNRS, rue du Capitaine Scott, “Combining text and image retrieval”.
[7]Kanchan Saxena, Vineet Richaria, Vijay Trivedi,“A Survey on Content Based Image Retrieval using BDIP, BVLC AND DCD”, Journal of Global Research in Computer Science , Vol.3, No. 9, September 2012 ,ISSN-2229-371X.
[8] Gaurav Jaswal Amit Kaul , “ Content Based Image Retrieval ”, National Conference on Computing, Communication and Control , A Literature Review , National Institute of Technology, Hamirpur-177001, Himachal Pradesh(India).
[9] R.Senthil Kumar, Dr.M.Senthilmurugan, “Content-Based Image Retrieval System in Medical”,International Journal of Engineering Research & Technology (IJERT),Vol. 2 Issue 3, March – 2013,ISSN: 2278-0181.
[10] Ivan Lee, Paisarn Muneesawang, Ling Guan, “Automatic Relevance Feedback for Distributed Content-Based Image Retrieval”,ICGST, FLEXChip Signal Processor (MC68175/D), Motorola, 1996.
[11] Paolo Parisen Toldin, “A survey on content-based image retrieval/browsing systems exploiting semantic”, 2010-09-13.
[12] M. Sifuzzaman, M.R. Islam and M.Z. Ali ,“Application of Wavelet Transform and its Advantages Compared to Fourier Transform ”, Journal of Physical Sciences, Vol. 13, 2009, 121-134 ISSN: 0972-8791.
[13] Pooja Verma, Manish Mahajan, “Retrieval of better results by using shape techniques for content based retrieval”,IJCSC ,Vol. 3, No.2, January-June 2012, pp. 254-257, ISSN: 0973-7391.
[14] Nidhi Singhai,Prof. Shishir K. Shandilya , “A Survey On: Content Based Image Retrieval Systems ”, International Journal of Computer Applications (0975 – 8887) Volume 4 – No.2, July 2010.

CBIR, GLCM, Image Texture, Color Spaces, Euclidean Distance, Image Retrieval, Precision, Recall.