Content-based image retrieval (CBIR) has been a subject of intensive research effort for more than a decade now. It differs from many of its neighboring research disciplines in computer vision due to one notable fact: human subjectivity cannot totally be isolated from the use and evaluation of CBIR systems. In addition, two more points make CBIR systems special. Opposed to such computer vision ...

Consistently the web and online media producing terabytes of images. Furthermore, picture stockpiling important recovery is a difficult task. Content Based Image Retrieval (CBIR) most common way recovering pertinent photos regarding query images from assortment CBIR profoundly relies upon three elements: determination, extraction, portrayal elements/features. The proposed review work discusses ...

The CBIR tends to index and retrieve images based on their visual content. CBIR avoid many evils connected with conservative ways of retrieve images by keywords. Thus, a rising interest in the area of CBIR has been known in current years. The arrangement of a CBIR system mainly depends on the particular image illustration and similarity matching function working. The CBIR tends to index and ret...

The general topic of my research, and thus also this annotated bibliography, is contentbased image retrieval (CBIR). Within CBIR, I picked out two areas that seem crucial to me: performance evaluation of CBIR systems and semantic scene understanding or scene categorization as a pre-step towards CBIR based on the automated annotation of scenes. In Section 2, some overviews of work done in CBIR a...

The inevitable growth in computer field brought a significant increase for storing large amount of images along with different kinds of complexity aspects. The need for efficient storage and retrieval of images has been recognized by having large image collections in the areas such as medicine, journalism, education, entertainment, advertisement, commerce, etc. The process of retrieving desired...

Validation of Remote Sensing Content-Based Information Retrieval (RS-CBIR) systems requires innovative strategies to overcome the scarcity of labeled data. CBIR systems validation by means of precision/recall measures based on either, user’s feedback or a-priori known categories, are hard to apply to RS-CBIR systems. We propose to apply a datadriven (unsupervised) quality assessment strategy an...

Content-based image retrieval (CBIR) technology has been proposed to benefit not only the management of increasingly large image collections, but also to aid clinical care, biomedical research, and education. Based on a literature review, we conclude that there is widespread enthusiasm for CBIR in the engineering research community, but the application of this technology to solve practical medi...

Content-based image retrieval (CBIR) addresses the problem of assisting a user to retrieve images from unannotated databases, based on features that can be automatically derived from the images. Today, there exists several CBIR systems based on different methods. Only few attemps to benchmark these have been made, although the usefulness of benchmarking is undeniable in the development of diffe...

Content-based image retrieval (CBIR) is a research area dedicated to address the retrieve and search multimedia documents for digital libraries. Relevance feedback is a powerful technique in CBIR and has been an active research topic for the past few years. In this paper, we review the current state-of-the-art of research on relevance feedbacks for CBIR and present the iFind system developed at...