Conventional image processing algorithms used to compare images are very timeconsuming, making them inappropriate for use in searching for an image in a huge collection of images ...
Caetano Traina Jr., Agma J. M. Traina, Rildo R. do...
This paper describes our participation in the Medical Image Retrieval task of Image CLEF 2008. Our aim was to evaluate different combination methods for purely textual and visual ...
Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...
This paper presents a robust technique for Content Based Image Retrieval (CBIR) using salient points of an image. The salient points are extracted from different levels of the uns...
In this paper, we present a novel image representation that renders it possible to access natural scenes by local semantic description. Our work is motivated by the continuing effo...