Semantic-based image retrieval has attracted great interest in recent years. This paper proposes a region-based image retrieval system with high-level semantic learning. The key features of the system are: (1) it supports both query by keyword and query by region of interest. The system segments an image into different regions and extracts low-level features of each region. From these features,...

Breast imaging case not only image low level features but also has image semantic features. In order to implement multimode retrieval of breast imaging, using feature selection algorithm based on association rules to select features, digging out the associated relationship between image low level features and image semantic features, and then taking advantage of association classification algor...

Most of the currently existing image retrieval systems make use of either low-level features or semantic (textual) annotations. A combined usage during annotation and retrieval is rarely attempted. In this paper, we propose a standardized annotation framework that integrates semantic and feature based information about the content of images. The presented approach is based on the MPEG-7 standar...

Medical image retrieval to search for clinically relevant and visually similar images depicting suspecious lesions have been attracting research interest. Content-based image retrieval (CBIR) is an important alternate and complement to traditional text-based retrieval using keywords. We have implemented CBIR system based on effective use of texture information within the images obtained by stat...

Medical image retrieval to search for clinically relevant and visually similar images depicting suspecious lesions have been attracting research interest. Content-based image retrieval (CBIR) is an important alternate and complement to traditional text-based retrieval using keywords. We have implemented CBIR system based on effective use of texture information within the images obtained by stat...

This work is about content based image database retrieval, focusing on developing a classification based methodology to address semantics-intensive image retrieval. With Self Organization Map based image feature grouping, a visual dictionary is created for color, texture, and shape feature attributes, respectively. Labeling each training image with the keywords in the visual dictionary, a class...

ABStrAct In content-based image retrieval (CBIR), a set of low-level features are extracted from an image to represent its visual content. Retrieval is performed by image example where a query image is given as input by the user and an appropriate similarity measure is used to find the best matches in the corresponding feature space. This approach suffers from the fact that there is a large dis...