Image-related interactions are forming an increasingly large part of modern communications, bringing the need for efficient and effective compression. Image compression is important for effective storage and transmission of images. Image processing applications are increasingly being done on embedded systems because image processing involves high computation and data requirements. This paper wo...

Content-based image indexing complexity often depends on image dimensions and data size. Reducing image dimensions before indexing affects the overall feature extraction and indexing complexity, as well as the retrieval performance. In this paper, the effects of Discrete Wavelet Transform (DWT) based downscaling on semantic retrieval performance are investigated via dedicated experiments. Sever...

Relevance feedback is an attractive approach to developing flexible metrics for content-based retrieval in image and video databases. Large image databases require an index structure in order to reduce nearest neighbor computation. However, flexible metrics can alter an input space in a highly nonlinear fashion, thereby rendering the index structure useless. Few systems have been developed that...

Image retrieval and image compression are each areas that have received considerable attention in the past. In this work, we present an approach for content-based image retrieval (CBIR) using vector quantization (VQ). Using VQ allows us to retain the image database in compressed form without any need to store additional features for image retrieval. The hope is that encoding an image with a cod...

This paper presents a new approach for building semantic image indexing and retrieval systems. Our approach is composed of four phases : (1) knowledge acquisition, (2) weakly-supervised learning, (3) indexing and (4) retrieval. Phase 1 is driven by a visual concept ontology which helps the expert to define low-level features useful to characterize object classes. Phase 2 uses acquired knowledge...

Automatic image annotation is an attractive approach for enabling convenient access to images found in a variety of documents. Since image captions and relevant discussions found in the text can be useful for summarizing the content of images, it is also possible that this text can be used to generate salient indexing terms. Unfortunately, this problem is generally domainspecific because indexi...

Content-based image retrieval (CBIR) aims at searching image databases for specific images that are similar to a given query image based on matching of features derived from the image content. This paper focuses on a low-dimensional color based indexing technique for achieving efficient and effective retrieval performance. In our approach, the color features are extracted using the mean shift a...