抽象的

Content Based Image Retrieval (CBIR) Using Segmentation Process

R.Gnanaraja, B. Jagadishkumar, S.T. Premkumar, B. Sunil kumar

Mining of Structured representations in content based image retrieval is a popular research topic in many useful applications. In the last decade there has been an explosion of interest in mining time series data. Literally hundreds of papers have introduced new algorithms to index, classify, cluster and segment time series. The initial work focused mainly on values with tags, while most of the recent development focuses on discovering association rule among tree structured data objects to preserve the structural information. In this paper we combined the techniques of texture based segmentation algorithm, Blob reduction by identifying outlier’s detection, SIFT algorithm to an automatic system to annotate and retrieve images. This paper tend to reveal a good behaviour in classification of our graph based solution on two publicly available databases and produce the images features with more enhancement by an efficient segmentation algorithm.