It is known that no single descriptor is powerful enough to encompass all aspects of image content, i.e. each feature extraction method has its own view of the image content. A pos...
Lin Mei, Gerd Brunner, Lokesh Setia, Hans Burkhard...
Retrieval in a multimedia database usually involves combining information from different modalities of data, such as text and images. However, all modalities of the data may not b...
Abraham Bagherjeiran, Nicole S. Love, Chandrika Ka...
Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...
Content-based image retrievalsystems use low-levelfeatures like color and texturefor image representation. Given these representationsasfeature vectors, similarity between images ...
Selim Aksoy, Robert M. Haralick, Faouzi Alaya Chei...
Recently, semantic image retrieval has attracted large amount of interest due to the rapid growth of digital image storage. However, existing approaches have severe limitations. I...