Feature Extraction for Image Mining


Due to the digitization of data and advances in technology, it has become extremely easy to obtain and store large quantities of data, particularly Multimedia data. Fields ranging from Commercial to Military need to analyze these data in an efficient and fast manner. Presently, tools for mining images are few and require human intervention. Feature selection and extraction is the pre-processing step of Image Mining. Obviously this is a critical step in the entire scenario of Image Mining. Our approach to mine from Images – to extract patterns and derive knowledge from large collections of images, deals mainly with identification and extraction of unique features for a particular domain. Though there are various features available, the aim is to identify the best features and thereby extract relevant information from the images. We have tried various methods for extraction; the features extracted and the techniques used are evaluated for their contribution to solving the problem. Experimental results show that the features used are sufficient to identify the patterns from the Images. The extracted features were evaluated for goodness and tested on test images. An interactive system was developed which allows the user to define new features and to resolve uncertain regions.

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@inproceedings{Foschi2002FeatureEF, title={Feature Extraction for Image Mining}, author={Patricia G. Foschi and Deepak Kolippakkam and Huan Liu and Amit Mandvikar}, booktitle={Multimedia Information Systems}, year={2002} }