Image mining is the process of searching and discovering valuable information and knowledge in large volumes of data. Image mining is simply an expansion of data mining in the field of image processing. Image mining handles with the hidden knowledge extraction, image data association and additional patterns which are not clearly accumulated in the images. Advances in image acquisition and storage technology have led to tremendous growth in significantly large and detailed image databases. These images, if analyzed, can reveal useful information to the human users. Image mining deals with the extraction of implicit knowledge, image data relationship, or other patterns not explicitly stored in the images. Image mining is more than just an extension of data mining to image domain. With significantly large and increasing multimedia database often the users have to mine the available data to retrieve the relevant information. Image Retrieval, which is an important phase in image mining, is one technique which helps the users in retrieving the data from the available database. The increase in number of images and image databases has given way for the need for image mining techniques. Image mining is an extended branch of data mining that is concerned with the process of knowledge discovery concerning digital images. The main aim of this paper is to present an overview of the various image mining applications like image retrieval, Matching, Pattern recognition etc.
1. Archana B. Waghmare, “Low-Level Feature Extraction for Content-Based Image Retrieval”, International Journal of Advances in Computing and Information Researches ISSN: 2277-4068, Volume 1–No.2, April 2012. 2. Bi, J, and J. Liang. “Multiple Instance Learning of Pulmonary Embolism Detection with Geodesic Distance along Vascular Structure.” Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’07). 2007. 3. Chang, S., et al., Semantic visual templates: linking visual features to semantics, in IEEE International Conference on Image Processing (ICIP’98), Chicago, Illinois, 1998, 531-535. 4. Corridoni, J, Bimbo A., Vicario E., Image retrieval by color semantics with incomplete knowledge, Journal of the American Society for Information Science 49(3), 1998, 267-282. 5. James Dowe. Content based retrieval in multimedia imaging. In Proc. SPIE storage and Retrieval for Image and Video Databases, 1993. 6. Dr.V.Mohan, A.Kannan, “Color Image Classification and Retrieval using Image mining Techniques”, International Journal of Engineering Science and Technology,Vol. 2(5), 2010. 7. W. Niblack, R. Barber, and et al. The QBIC project: Querying images by content using color, texture and shape. In Proc. SPIE Storage and Retrieval for Image and Video Databases, Feb 1994. 8. Patricia G. Foschi, Deepak Kolippakkam, “Feature Extraction for Image Mining”. 9. U.Ravindran,T.Shakila ,”Content Based Image Retrieval For Histology Image Collection Using Visual Pattern Mining”, International Journal of Scientific & Engineering Research, Volume 4, Issue 4, April-2013. 10. Y. Rui, T. Huang and S. Chang. Image retrieval: current techniques, promising directions and open issues. Journal of Visual Communication and Image Representation, 10(4): 39-62, April 1999. 11. Sharlee Climer, Sanjiv K. Bhatia. Image Database indexing using JPEG coefficients. The journal of the Pattern Recognition Society, Pattern Recognition 35 (2002) 2479-2488. 12. S. F. Chang and J.R. Smith. Extracting Multi-Dimensional Signal Features for Content- Based Visual Query. SPIE Symposium on Visual Communications and Signal Processing, May 1995. 13. Swati V. Sakhare , Vrushali G. Nasre, “Design of Feature Extraction in Content Based Image Retrieval (CBIR) using Color and Texture”, International Journal of Computer Science & Informatics,Volume-I, Issue-II, 2011. 14. Wu, D, J Bi, and K Boyer. “A Min-Max Framework of Cascaded Classifier with Multiple Instance Learning for Computer Aided Diagnosis.” Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR’09). 2009. 15. Zhang Ji, Hsu, Mong, Lee, Image Mining: Issues, Frameworks And Techniques, Proceedings of the Second International Workshop on Multimedia Data Mining (MDM/KDD’2001), in conjunction with ACM SIGKDD conference. San Francisco, USA, August 26, 2001.