Satellite images have gained a wide popularity in the field of content-based image retrieval. A massive amount of these images are collected every year due to the high availability of satellites and computer technologies. However, extracting user-specific content from these images still remains a primary concern due to the presence of semantic gap. This limits the capabilities of CBIR. Therefor...

In this research ,we develop a facial image retrieval computational model for the problem of facial images retrieval by integrating content-based image retrieval (CBIR) techniques and face recognition techniques(FERET) , with the verbal description of the semantic features of the facial image . Eigenfaces is applied to extract the characteristic feature images of the human face images. One hund...

This paper addresses the issue of retrieving images based on visual content, according a particular attention to the semantic dimension of information retrieval. A brief review of existing Image Retrieval Systems is provided, hilighting a major drawback of these prototypes, namely the lack of integration between classical \semantic search", and visual similarity retrieval (i.e. content-based re...

Current image retrieval techniques have shortcomings that make it difficult to search for images based on a semantic understanding of what the image is about. Since an image is normally associated with multiple contexts (e.g. when and where a picture was taken,) the knowledge of these contexts can enhance the quantity of semantic understanding of an image. In this paper, we present a context-aw...

image retrieval is an important research field which has received great attention in the last decades. in this paper, we present an approach for the image retrieval based on the combination of text-based and content-based features. for text-based features, keywords and for content-based features, color and texture features have been used. query in this system contains some keywords and an input...

In this demonstration, a two-level system for semantic-based image retrieval is proposed. To overcome the shortcoming of the traditional retrieval system, we present a novel method which can provide effective retrieval result in a short time. Firstly, it uses surrounding text to get a related candidate image set. Secondly, a semantic network is used to map the keyword to one of concept models w...

Image retrieval systems play a key role in big image database systems. User may search for the image using keywords, phrases or image itself. CBIR approaches helps to retrieve image based on the contents or features of the image. RBIR approach helps to retrieve images based on the regions.The images retrieved using RBIR have more close similarity with human approaches.But the semantic gap still...

p. 1 Exploring the Stability of IDF Term Weighting p. 10 Completely-Arbitrary Passage Retrieval in Language Modeling Approach p. 22 Semantic Discriminative Projections for Image Retrieval p. 34 Comparing Dissimilarity Measures for Content-Based Image Retrieval p. 44 A Semantic Content-Based Retrieval Method for Histopathology Images p. 51 Integrating Background Knowledge into RBF Networks for T...