Traditional content-based image retrieval (CBIR) systems often fail to meet a user's need due to the `semantic gap' between the extracted features of the systems and the...
We present a novel framework for intelligent search and retrieval by image content composition. Very different from the existing Query-by-Example paradigm, logical queries are exp...
We propose a neural network based method for organizing images for content-based image retrieval. We use spectral histogram features, the histograms of filtered images to capture...
In this paper, an image retrieval methodology suited for search in large collections of heterogeneous images is presented. The proposed approach employs a fully unsupervised segme...
Vasileios Mezaris, Ioannis Kompatsiaris, Michael G...
In recent years, some computer vision algorithms such as SIFT (Scale Invariant Feature Transform) have been employed in image similarity match to perform image-based search applic...