Content-based image retrieval (CBIR) is a new but widely espoused method for finding images from enormous image databases. The need of content based image retrieval technique is in different domains such as medical imaging, crime prevention, weather forecasting, surveillance, historical research and remote sensing. This paper presents the content based image retrieval, using texture and color f...

In this paper we present a new approach to image indexing and retrieval based on image correlogram. We show that in comparison with usually used approaches, i.e. image histogram and autocorrelogram, image correlogram gives significantly better results in image retrieval. These results are achievable without increasing computational cost in image indexing or retrieval. In the experimental part o...

The increasing prevalence of broadband Internet access is making it easier to obtain rich contents like images, and more people are attempting image retrieval. We focus on how to present web image retrieval results to users. Most retrieval results contain multiple topics. To offset this complexity, many papers have discussed text retrieval result clustering [11][14]. In result clustering, we cl...

This paper provides an overview of current research in image information retrieval and provides an outline of areas for future research. The approach is broad and interdisciplinary and focuses on three aspects of image research (IR): text-based retrieval, content-based retrieval, and user interactions with image information retrieval systems. The review concludes with a call for image retrieval...

In this paper we present image data representation, similarity image retrieval, the architecture of a generic content-based image retrieval system, and different content-based image retrieval systems.

In this paper, we present an effective approach for improving content-based image retrieval (CBIR) with relevance feedback. A rectangular image segmentation technique is used for feature extraction in image retrieval. Then an image object matching algorithm is proposed for image retrieval. Finally, a feature reweighting approach is used for relevance feedback, which transforms object features i...

Describing and extracting image’s feature is a key question in content-based image retrieval system, and this paper puts forward a novel image retrieval method using image information entropy and fractal coding. First, compared with a given threshold computed from the inquired image, each image in the database is classified by computing its image entropy. Second, the inquired image’s fractal co...