Abstract

Although there has been massive research work being conducted in the area of content-based image retrieval (CBIR) system using various sophisticated techniques, very little work has been witnessed for visual art images. From the literatures, it has also been witnessed that clustering algorithm has played a big role in justifying the outcome of various CBIR system. The objective of the proposed system is to introduce a new clustering technique which is implemented over a large set of visual art images. The proposed algorithm is implemented and its performance is measured with respect to two performance parameter namely,. recall and precision. The accomplished outcome of the study is also compared with two conventional clustering techniques that are frequently seen on literatures to understand where the proposed system stands. The accomplished results were seen to outperform conventional clustering technique.

References

• Antani, S. , Long, L. R. , Thomas, G. R2004. Content-Based Image Retrieval for Large Visual art Image Archives, MEDINFO
• Murthy, V. S. V. S. 2010. Content based image retrieval using Hierarchical and K-means clustering techniques, International Journal of Engineering Science and Technology 2. 3,pp. 209-212
• Tonge, Vanita G. 2011. Content based image retrieval by K-Means clustering algorithm. " Int J Eng Sci Tech,Vol. 2, pp. 209-212
• Analoui, M. , Beheshti, M. 2011. Content-based Image Retrieval Using Artificial Immune System (AIS) Clustering Algorithms, In Proceedings of the International MultiConference of Engineers and Computer Scientists, Vol. 1
• Samathal, S. , Mohanraj, N. 2010. BTC with K means classifier using color image clustering". Journal of Computer Application, 5
• Murthy, V. S. V. S. , Vamsidhar, E. , Rao, P. S. , Raju, G. S. V. 2010. Application of hierarchical and K-means techniques in Content based image retrieval, International Journal of Engineering Science and Technology,Vol. 2(5), pp. 749-755
• Balan, S. , Devi, T. 2012. Design and Development of an Algorithm for Image Clustering In Textile Image Retrieval Using Color Descriptors, International Journal of Computer Science, Engineering and Applications (IJCSEA), Vol. 2(3)
• Huu, Q. N. , Thu, H. N. T. , Quoc, T. N. 2012. An efficient content based image retrieval method for retrieving images, International Journal Of Innovative Computing Information And Control,Vol. 8(4), pp. 2823-2836
• Malakar, A. , Mukherjee, J. 2013. Image Clustering using Color Moments, Histogram, Edge and K-means Clustering, International Journal of Science and Research (IJSR), India Online ISSN: 2319-7064
• Komali, A. , Babu, R. V. 2013. An Efficient Content Based Image Retrieval System for Color and Shape Using Optimized K-Means Algorithm, International Journal of Application or Innovation in Engineering & Management (IJAIEM),Vol. 2, Issue. 8
• Jadhav, S. H. , Ahmed, S. A. 2012. A Content Based Image Retrieval System using homogeneity Feature extraction from Recency-based Retrieved Image Library, IOSR Journal of Computer Engineering (IOSRJCE), Vol. 7, Issue. 6, pp. 13-24
• Ravindran, U. , Shakila, T. 2013. Content Based Image Retrieval For Histology Image Collection Using Visual Pattern Mining, International Journal of Scientific & Engineering Research, Vol. 4, Issue 4, 2013
• Raghatate, K. S. , Janwe, J. 2013. Content Based Image Retrieval With Relevance Feedback Using Clustering, International Journal of Recent Advances in Engineering & Technology (IJRAET) ISSN, Vol. 1, Issue -2
• R. Xu and D. Wunsch. 2005. Survey of clustering algorithms, IEEE Transactions on Neural Networks, Vol. 16, Issue 3, pp. 645– 678
• V. K. Garg. 2009. Pragmatic data mining: Novel paradigms for tackling key challenges, Project Report, Computer Science & Automation (CSA), Indian Institute of Science
• http://guides. library. yale. edu/content. php?pid=47735&sid=354520
• Silakari, S. , Motwani, M. , Maheshwari, M. 2009. Color Image Clustering using Block Truncation Algorithm, IJCSI International Journal of Computer Science Issues, Vol. 4, No. 2, 2009
• Prasad, B. G. , K. K. Biswas, and S. K. Gupta. 2004Region-based image retrieval using integrated color, shape, and location index, Computer vision and image understanding, Vol. 94(1),pp. 193-233.