This paper deals with content-based image retrieval. When the user is looking for large categories, statistical classification techniques are efficient as soon as the training se...
Matthieu Cord, Philippe Henri Gosselin, Sylvie Phi...
In this paper, we propose a new type of image feature, which consists of patterns of colors and intensities that capture the latent associations among images and primitive feature...
In this paper, we present the results of a project that seeks to transform low-level features to a higher level of meaning. This project concerns a technique, latent semantic inde...
We have developed a novel system for content-based image retrieval in large, unannotated databases. The system is called PicSOM, and it is based on tree structured self-organizing...
Jorma Laaksonen, Markus Koskela, Sami Laakso, Erkk...
Content-based image retrieval in astronomy needs methods that can deal with an image content made of noisy and diffuse structures. This motivates investigations on how information ...
We investigate the properties of a metric between two distributions, the Earth Mover's Distance (EMD), for content-based image retrieval. The EMD is based on the minimal cost ...
Content-based image retrieval plays an important role in many multimedia applications. Images are typically retrieved based on a given sample image, a sketch or a simple descripti...
This study presents a content-based image retrieval system IMALBUM based on local region of interest called object of interest (OOI). Each segmented or user-selected OOI is indexe...
Object recognition and content-based image retrieval systems rely heavily on the accurate and efficient identification of shapes. A fundamental requirement in the shape analysis p...
Dragomir Yankov, Eamonn J. Keogh, Li Wei, Xiaopeng...