Content-based image retrieval (CBIR) is widely adopted method for finding images from vast collection of images in the database. As the collections of images are growing at a rapid rate, demand for efficient and effective tools for retrieval of query images from database is increased significantly. Among them, content-based image retrieval systems (CBIR) have become very popular for browsing, s...

Image retrieval has been popular for several years. There are different system designs for content based image retrieval (CBIR) system. This paper propose a novel system architecture for CBIR system which combines techniques include content-based image and color analysis, as well as data mining techniques. To our best knowledge, this is the first time to propose segmentation and grid module, fe...

Content-based image retrieval (CBIR) refers to the use of visual features for images retrieval, and has become an attractive approach to managing biomedical image achieves. However, existing CBIR systems are typically designed for 2D single-modality imaging, and are restricted when multi-dimensional images are considered. With the advances in imaging scanners, image complexity and magnitude hav...

In this pape,: a new image feature extraction method based on the statistical analysis in the wavelet domain is developed for content-based image retrieval (CBIR). A !WO component Gaussian mixture model is developed to describe the statitistical characteristics of images in the wavelet domain. The model parameters are obtained by an EM (Expectation-Maximization) algorithm and then employed to c...

In this technical report we introduce and describe the MultimediaRetrievalMarkup Language (MRML). This XML-based markup language is the basis for an open communication protocol for content-based image retrieval systems (CBIRSs). MRML was initially designed as a means of separating CBIR engines from their user interfaces. It is, however, also extensible as the basis for standardized performance ...

Content based image Retrieval (CBIR) has been an active research field since the past two decades. In contrast to a traditional system, in which the images are retrieved based on the keywords, CBIR system retrieves the images based on the visual content. In this paper, we start with the introduction to a simple CBIR system and proceed to review few of the techniques used to develop CBIR system....

In a Content Based Image Retrieval (CBIR) System, the task is to retrieve similar images from large database given query image. The usual procedure extract some useful features image, and which have set of features. For this purpose, suitable similarity measure chosen, with high scores are retrieved. Naturally choice these play very important role in success system, level required reduce semant...

Content based Image retrieval is a process which will enhance the image searching accuracy. Many researchers are working on image processing. CBIR approach uses different techniques such as colour, texture and shape, by processing this feature vector is generated and comparison is done. CBIR approach can be used in many places such as search engines, patent registration, face detection etc. CBI...

Image annotation and retrieval has been a popular research topic for decades. Based on published journals from 2012 until 2015, a lot of research and studies has been focused on Content Based Image Retrieval (CBIR). In most cases, CBIR systems that use an image as the input query always face a problem called semantic gap due to the use of low-level features for similarity matching. The semantic...

Content-based image retrieval (CBIR) technologies offer many advantages over purely text-based image search. However, one of the drawbacks associated with CBIR is the increased computational cost arising from tasks such as image processing, feature extraction, image classification, and object detection and recognition. Consequently CBIR systems have suffered from a lack of scalability, which ha...