This paper adopts the premise that the ‘semantic gap' is an incompletely surveyed feature in the landscape of visual image retrieval, and proposes a framework within which t...
Use of semantic content is one of the major issues which needs to be addressed for improving image retrieval effectiveness. We present a new approach to classify images based on t...
We consider the problem of modeling annotated data—data with multiple types where the instance of one type (such as a caption) serves as a description of the other type (such as...
Image retrieval based on content from digital libraries, multimedia databases, the Internet, and other sources has been an important problem addressed by several researchers. In t...
Recent research effort in Content-Based Image Retrieval (CBIR) focuses on bridging the gap between low-level features and highlevel semantic contents of images as this gap has bec...
Mei-Ling Shyu, Shu-Ching Chen, Min Chen, Chengcui ...
Conventional approaches to image retrieval are based on the assumption that relevant images are physically near the query image in some feature space. This is the basis of the clu...
In this demonstration, we present an image retrieval system to support multimedia authoring and presentation. An affinity-based mechanism, Markov Model Mediator (MMM), is used as ...
Shu-Ching Chen, Mei-Ling Shyu, Na Zhao, Chengcui Z...
In this paper, we propose a semantic-meaningful approach for region-based image retrieval in image database. Our retrieval system is based on wavelet transform for its decompositi...
In a typical content-based image retrieval (CBIR) system, query results are a set of images sorted by feature similarities with respect to the query. However, images with high fea...
Content-Based Image Retrieval (CBIR) systems have been developed aiming at enabling users to search and retrieve images based on their properties such as shape, color and texture....
Ricardo da Silva Torres, Eduardo M. Picado, Alexan...