𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Qualitative part-based models in content-based image retrieval

✍ Scribed by Guillaume-Alexandre Bilodeau; Robert Bergevin

Publisher
Springer-Verlag
Year
2007
Tongue
English
Weight
790 KB
Volume
18
Category
Article
ISSN
0932-8092

No coin nor oath required. For personal study only.

πŸ“œ SIMILAR VOLUMES

Edge based features for content based im
Edge based features for content based image retrieval
✍ Minakshi Banerjee; Malay K. Kundu πŸ“‚ Article πŸ“… 2003 πŸ› Elsevier Science 🌐 English βš– 854 KB

The common problem in content based image retrieval (CBIR) is selection of features. Image characterization with lesser number of features involving lower computational cost is always desirable. Edge is a strong feature for characterizing an image. This paper presents a robust technique for extracti

Long-term learning in content-based imag
Long-term learning in content-based image retrieval
✍ Jing Li; Nigel M. Allinson πŸ“‚ Article πŸ“… 2008 πŸ› John Wiley and Sons 🌐 English βš– 476 KB

## Abstract In content‐based image retrieval, relevance feedback is an interactive process, which builds a bridge to connect users with the search engine. It leads to much improved retrieval performance by updating the query and the similarity measure according to a user's preference; and recently

Combining similarity measures in content
Combining similarity measures in content-based image retrieval
✍ Miguel Arevalillo-HerrΓ‘ez; Juan Domingo; Francesc J. Ferri πŸ“‚ Article πŸ“… 2008 πŸ› Elsevier Science 🌐 English βš– 296 KB

The purpose of content based image retrieval (CBIR) systems is to allow users to retrieve pictures from large image repositories. In a CBIR system, an image is usually represented as a set of low level descriptors from which a series of underlying similarity or distance functions are used to conveni