The paper addresses the issue of searching for similar images and objects ina repository of information. The contained images are annotated with the helpof the sparse descriptors. In the presented research, different color and edgehistogram descriptors were used. To measure similarities among images, variouscolor descriptors are compared. For this purpose different distance measureswere employed. In order to decrease execution time, several code optimizationand parallelization methods are proposed. Results of these experiments, as wellas discussion of the advantages and limitations of different combinations ofmethods are presented
AbstractFeature extraction and matching is at the base of many computer vision problems, such as obj...
Within the scope of information retrieval, efficient similarity search in large document or multimed...
Color has been widely used in content-based image retrieval (CBIR) applications. In such application...
The paper addresses the issue of searching for similar images and objects ina repository of informat...
The paper addresses the issue of searching for similar images and objects in arepository of informat...
Abstract The paper addresses the issue of searching for similar images and objects in a repository o...
In this paper, we propose a parallel similarity search strategy based on the dimensions value cardin...
In the context of content-based image retrieval from large databases, traditional systems typically ...
The task of searching and recognizing objects in images has become an important research topic in th...
Computer vision research enables machines to understand the world. Humans usually interpret and anal...
The algorithmical architecture and structure is presented for the parallelization of image similarit...
[[abstract]]The amount of pictorial data grows enormously with the expansion of the World Wide Web. ...
This report addresses precise image search based on local descriptors. Our approach extends a k-NN v...
International audienceTraditional content-based image retrieval systems typically compute a single d...
A new algorithm is presented which approximates the perceived visual similarity between images. The ...
AbstractFeature extraction and matching is at the base of many computer vision problems, such as obj...
Within the scope of information retrieval, efficient similarity search in large document or multimed...
Color has been widely used in content-based image retrieval (CBIR) applications. In such application...
The paper addresses the issue of searching for similar images and objects ina repository of informat...
The paper addresses the issue of searching for similar images and objects in arepository of informat...
Abstract The paper addresses the issue of searching for similar images and objects in a repository o...
In this paper, we propose a parallel similarity search strategy based on the dimensions value cardin...
In the context of content-based image retrieval from large databases, traditional systems typically ...
The task of searching and recognizing objects in images has become an important research topic in th...
Computer vision research enables machines to understand the world. Humans usually interpret and anal...
The algorithmical architecture and structure is presented for the parallelization of image similarit...
[[abstract]]The amount of pictorial data grows enormously with the expansion of the World Wide Web. ...
This report addresses precise image search based on local descriptors. Our approach extends a k-NN v...
International audienceTraditional content-based image retrieval systems typically compute a single d...
A new algorithm is presented which approximates the perceived visual similarity between images. The ...
AbstractFeature extraction and matching is at the base of many computer vision problems, such as obj...
Within the scope of information retrieval, efficient similarity search in large document or multimed...
Color has been widely used in content-based image retrieval (CBIR) applications. In such application...