Content-based image retrieval (CBIR) is currently limited because of the lack of representational power of the low-level image features, which fail to properly represent the actual...
Abstract. The proposed work exploits methods and techniques for automatic characterization of images for content-based access to personal photo libraries. Several techniques, even ...
Content-based image retrieval (CBIR) systems target database images using feature similarities with respect to the query. Our CBIR demonstration utilises novel illumination invari...
In this paper, we outline some of the main challenges facing trademark searchers today, and discuss the extent to which current automated systems are meeting those challenges. Cat...
One key challenge in content-based image retrieval (CBIR) is to develop a fast solution for indexing high-dimensional image contents, which is crucial to building large-scale CBIR...
This paper presents a new relevance feedback method for content-based image retrieval using local image features. This method adopts a genetic programming approach to learn user p...
Jefersson Alex dos Santos, Cristiano D. Ferreira, ...
In this article we focus on the presentation of the inner structure of the database for the Content-Based Image Retrieval (CBIR) system containing house images. The part devoted t...
Abstract. In content-based image retrieval (CBIR) and image screening, it is often desirable to locate the regions of interest (ROI) in the images automatically. This can be accomp...
Yu-Feng Li, James T. Kwok, Ivor W. Tsang, Zhi-Hua ...
— In this paper, we present a novel relevance feedback method for Content-Based Image Retrieval systems based on dynamic feature weights. The proposed method utilizes intracluste...
In order to bridge the “Semantic gap”, a number of relevance feedback (RF) mechanisms have been applied to content-based image retrieval (CBIR). However current RF techniques i...
Haiming Liu 0002, Victoria S. Uren, Dawei Song, St...