A Literature Survey on Image Mining

In this paper, the overview of the Image Mining and its techniques are surveyed. This paper imparts more number of applications of the data mining. 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 –is to extract patterns and derive knowledge from large collection 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. Various methods for extraction are used in this paper. Content Based Image Retrieval is the popular image retrieval method by which the target image is to be retrieved based on the useful features of the given image. In this paper, the concepts of Content Based Image Retrieval and Image mining have been combined and a new clustering technique has been introduced in order to increase the speed of the image retrieval method. Experimental results show that the features here used are sufficient to identify the patterns from the Images. The extracted features are evaluated for goodness and are tested on the images. This paper presents a survey on various image mining techniques that were proposed earlier in literature.