Integrated Region-Based Image Retrieval
The need for efficient content-based image retrieval has increased tremendously in areas such as biomedicine, military, commerce, education, and Web image classification and searching. In the biomedical domain, content-based image retrieval can be used in patient digital libraries, clinical diagnosis, searching of 2-D electrophoresis gels, and pathology slides. \ Integrated Region-Based Image Retrieval presents a wavelet-based approach for feature extraction, combined with integrated region...
Search in google:
Content based image retrieval is the set of techniques for retrieving relevant images from an image database on the basis of automatically derived image features. Wang (Pennsylvania State U.) explains the CBIR system, designed by him and his colleagues, that utilizes wavelet- based feature extraction, semantics classification, and integrated region matching. Images are represented by sets of regions, characterized by color, texture, shape, and location and are then classified into semantic categories. This enhances semantically-adaptive searching methods by narrowing down the searching range within the database. Wang believes that his methods will have many applications, especially in the biomedical fields. Annotation c. Book News, Inc., Portland, OR (booknews.com)
PrefaceAcknowledgments1Introduction12Background173Wavelets394Statistical Clustering and Classification495Wavelet-Based Image Indexing and Searching636Semantics-Sensitive Integrated Matching857Image Classification by Image Matching1058Evaluation1239Conclusions and Future Work159References165Index177
