The whole world is filled with a huge collection of digital data, digital images, and videos or can be anything that can be stored in a digitized manner. This data doesn`t mean essentially anything. It is stored in an unorganized manner without any interpretation. Image Mining is an energetic concept for researchers. When there is a need to extract necessary information from the massive collection of image database through image mining techniques then this concept came into the picture. In this research paper, the proposed work is done through two steps. One is feature extraction, extract the features of images by RGBHist as a color feature and Edge Histogram Descriptor as a shape feature has taken to create feature dataset. While in second step K-Medoid clustering algorithm is applied to make good clusters and retrieval process is done from the clusters to increase the accuracy of the system. Manhattan similarity method is used a matching purpose from the query image. Three Database is used in this paper for testing the proposed image mining system.

Image Mining, RGB histogram descriptor, Edge Histogram Descriptor (EHD), Content Based Image Retrieval (CBIR), Clustering, K-Medoid Clustering Algorithm, Data Mining, Manhattan Similarity Measure,

[1] Maria Fayez, Soha Safwat and Ehab Hassanein,"Comparative Study of Clustering Medical Images”, 978-1-4673-8460-5/16 IEEE, SAI Computing Conference, London, UK, pp. 312–318
[2] Snehal Mahajan, Dharamaraj Patil, ”Image Retrieval Using Contribution-based Clustering”, Algorithm with Different Feature Extraction Techniques”978-1-4799-3064-7/14 IEEE
[3] Ruziana Mohamad Rasli, T Zalizam et al,"Comparative Analysis of Content Based Image Retrieval Technique using Color Histogram. A Case Study of GLCM and K-Means Clustering”, 978-0-7695-4668-1/12 IEEE DOI 10.1109/ISMS.2012.111
[4] Y. Poornima, P.S. Hiremath,”Efficient Modelling of Visual Art Color Image Clustering”, International Journal of Computer Applications (0975 – 8887) Volume 91 – No.11, April 2014
[5] Geethu Varghese, Dr. Arun Kumar M N "Content Based Image Retrieval using Feature Extraction and K-Means Clustering" International Journal for Innovative Research in Science and Technology Vol.3, ISSN:04 September(2016)-4238, pp.291-302
[6] Rupinder Kaur, Navleen Kaur,”Content Based Image Mining Technique for Image Retrieval Using Optimized Hybrid Clustering”, International Journal of Computer Trends and Technology (IJCTT) – Volume 11 number 3 – May 2014
[7] Ankita Tripathi, Shivam Pandey,”An Improved and Efficient Image Mining Technique for Classification of Textual Images Using Low-Level Image Features”, 10.1109@inventive.2016.7823220
[8] Amit Khatami, and Saeed Mirghasemi,"A New Color Space Based on K-medoids Clusterings for Fire Detection", 978-1--4799-8697-2/15, IEEE, DOI 10.1109/SMC. 2015.481,pp 2755-2760
[9] Katta Sugamya, Suresh Pabboju, Dr. A.VinayaBabu.” A CBIR Classification using support vector machines”, International Conference on Advances in Human Machine Interaction (HMI - 2016), 978-1-4673-8810-8/16 IEEE.
[10] Monika Sahu, Madhup Shrivastava “Image Mining: A New Approach for Data Mining Based on Texture”, 978-0-7695-4872-2/12 IEEE DOI 10.1109/ICCCT.2012.11
[11] Dong Kwon Park, Yoon Seok Jeon, and Chee Sun Won, ” Efficient Use of Local Edge Histogram Descriptor," ACM workshop on Multimedia, November 2000, pp. 51-55
[12] Sawet Somnupong,and Kanokwan Khiewwan,”Content –Based Image Retrieval using a Combination of Color Correlograms and Edge Direction Histogram,",JESSE,978-1-5090-2033-1/16 IEEE.
[13] Aruna Bhat, “K-Medoids Clustering Using Partitioning Around Medoids For Performing Face Recognition," IJSCMC, Vol 3, No 3, August 2014, DOI: 10.14810/IJSCMC.(2014).3301,pp-1-12
[14] Swarndeep Saket J. and. Sharnil Pandya,"Implementation of Extended K-Medoids Algorithms to Increase Efficiency and Scalability using Large Dataset", International Journal of Computer Applications(0975-8887) Volume 146- No. 5, July (2016),pp-19-23
[15] Prabhjeet Kaur and Kamaljit kaur, "Review of Different Existing Image Mining Techniques," International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE), Volume 4, Issue 6 June (2014), pp 518-524
[16] Swati Agarwal, A.K. Verma, Preetvanti Singh,”Content Based Image Retrieval using Discrete Wavelet Transform and Edge Histogram Descriptor”, 978-1-4673-5986-3, (2013), IEEE
[17] Priti Maheshwary, and Namita Srivastav “Retrieving Similar Image Using Color Moment Feature Detector and K-means Clustering of Remote Sensing Image,” 978-0-7695-3504-3/08, IEEE
[18] Neethu Joseph.c, Aswathy Wilson," Retrieval of Images using Data Mining Techniques”,978-1-4799-6629-5/14 IEEE

[19] Yogita Mistry, D. T. Ingole, and M. D. Ingole,” Efficient Content Based Image Retrieval Using Transform and Spatial Feature Level Fusion”, The 2nd International Conference on Control, Automation and Robotics. 978-1-4673-9859-61/16 IEEE.
[20] Naveena A K and N K Narayanan,"Image Retrieval using Combination of Color, Texture and Shape Descriptor,"©(2016) IEEE, pp-958-962
[21] Ming Zhang, Ke Zhang,and Qinghe Feng, Jianzhong Wang,Jun Kong and Yinghua Lu," A novel image retrieval based on hybrid information descriptors,”1047-3203/©(2014)Elsevier.
[22] Clustering- J. A. Hartigan, “Clustering Algorithms”, JohnWiley & Sons, 1975.
[23] [9] P. Arabie, L. J. Hubert, and G. De Soete, “Clustering and Classification”, World Scientific, 1996.
[24] Shubhangi P. Meshram, Dr. Anuradha D. Thakre,and Prof. Santwana Gudadhe “Hybrid Swarm Intelligence Method for Post Clustering Content Based Image Retrieval,” 7th International Conference on Communication Computing and Virtualization (2016), Elsevier B.V., pp. 509–515.
[25] Rajkumar Jain, and Punit Johari, ”An Improved Approach of CBIR using Color Based HSV Quantization and Shape Based Edge Detection Algorithm,” 978-1-5090-0774-5/16 ©2016 IEEE
[26] Jaimala Jha Dr. Sarita Sign Bhaduaria “Review of Various Shape Measures for Image Content Based Retrieval” International Journal of Computer & Communication Engineering Research Nov. (2015).
[27] Ravi Devesh, Jaimala Jha,”An Efficient Approach for Monuments Image Retrieval using Multi-Visual Descriptors.” In MCCS (2017),unpublished
[28] Jaimala Jha, Dr. Sarita Sign Bhaduaria “ Review of Various Shape Measures for Image Content Based Retrieval ” International Journal of Computer & Communication Engineering Research, Nov (2015).
[29] Ruchi Jayaswal, Jaimala Jha,"A Hybrid Approach For Image Retrieval using Visual Descriptors”, ISBN: 978-1-5090-6471-7/17/$31.00 ©(2017) IEEE, unpublished
[30] Rupali Sawant,”Image Mining Using Texture and Shape Feature”, International Journal of Computer Sciences and Engineering, Vol 02, No. 09, 2010, 2808-2815
[31] Ansari Mohd Aquib, Dixit Manish,”An Image Retrieval Framework: A Review", International Journal of Advanced Research in Computer Science,[S.l.], v. 8, n. 5, p. 692-699, June 2017. ISSN 0976-5697.