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...
One of the fundamental problems in Content-Based Image Retrieval (CBIR) has been the gap between low-level visual features and high-level semantic concepts. To narrow down this gap...
: Advances in data storage and image acquisition technologies have enabled the creation of large image datasets. In this scenario, it is necessary to develop appropriate informatio...
Performance evaluation of content-based image retrieval (CBIR) systems is an important but still unsolved problem. The reason for its importance is that only performance evaluatio...
Semantic-based image retrieval has attracted great interest in recent years. This paper proposes a region-based image retrieval system with high-level semantic learning. The key f...
Abstract Image retrieval has nowadays several industrial applications. In these imaging applications, which typically use large image archives, the matter of computational efficien...
Abstract This paper presents an approach to designing and implementing extensible computational models for perceiving systems based on a knowledge-driven joint inference approach. ...
In content-based image retrieval (CBIR), relevant images are identified based on their similarities to query images. Most CBIR algorithms are hindered by the semantic gap between ...
Luo Si, Rong Jin, Steven C. H. Hoi, Michael R. Lyu
—This paper presents a novel hybrid method for content based visual information retrieval (CBIR) that combines shape analysis of objects in image with their automatic indexing by...
We investigated image retrieval using texture segmentation by genetic programming. In this study, we are interested with two textures: sky and grass textures. Single-step texture ...