Learn More
Physicians create Medical Image Libraries (MILs) to collect typical case images, and utilize CBIR (Content-based Image Retrieval) tools to search feature-similar samples within them to aid clinical intervention and diagnoses. This paper presents a CSBIR (Content and Semantic Context based Image Retrieval) scheme for MedlmGrid (Medical Image Grid) to tackle(More)
This paper proposes a new re-ranking scheme and presents experimental performance results for Web image retrieval with integrated query. In our previous work, cross-modal association rule was designed for associating one keyword with several visual feature clusters in Web image retrieval. Based on the cross-modal association rule, we implement an automatic(More)
Image segmentation is an important task in many applications. For large-scale, general image dataset, however, there are the competing requirements, including not making complex prior assumptions about the scene, having fast speed and good segmentation quality. In this paper, a hybrid approach for image segmentation is presented that incorporates two famous(More)
Text-based image search engine and content-based image retrieval (CBIR) have achieved much progress in commercial and academic community respectively. However, few attempts have been conducted to integrate the two techniques for image retrieval in web context. In this paper, based on a novel web image data model, i.e. Fine-Grained Web Image Model (FGWIM), a(More)
Edge detection is arguably the most important operation in low level computer vision. Mean shift is an effective iterative algorithm widely used in edge detection. But the cost of computation prohibits Mean shift algorithm for high dimensions feature space. In this paper, a fast adaptive mean shift algorithm is proposed for edge detection. It makes use of(More)
To alleviate the known semantic gap, it is necessary to integrate the two-modal parts of Web images, i.e. the low-level visual features and high-level semantic concepts (which are usually represented by keywords), for Web image retrieval. In this paper, we associate the keyword and visual features of Web images from a different prospective and a new(More)
The associations between different modalities of Web images could be very useful for Web image retrieval. In this paper, we investigate the multi-modal associations between two basic modalities of web images, i.e. keyword and visual feature clusters, by data mining technique. The association rule crosses two modalities, in which the antecedent is a single(More)
Content-based image retrieval (CBIR) on the Web is an active research topic in recent years. However, a common problem for the content-based search is the difficulty for getting a query image, which dramatically limits the popularity of their application. The ubiquity of camera phones has opened up a new avenue for image-based mobile search and it also(More)