Information retrieval is the indexing and retrieving of data that match criteria specified by users. In today’s age, the proliferation of multimedia information makes it necessary to revolutionise traditional type of information retrieval systems. Content Based Image Retrieval (CBIR) is a research area attempting to address this issue. It is primarily concerned with using content-based informat...

Content-based image retrieval (CBIR) has been proposed as key technology for computer-aided diagnostics (CAD). This paper reviews the state of the art and future challenges in CBIR for CAD applied to clinical practice.We define applicability to clinical practice by having recently demonstrated the CBIR system on one of the CAD demonstration workshops held at international conferences, such as S...

Content-Based Image Retrieval (CBIR) systems retrieve images from the image repository or database in which they are visually similar to query image. CBIR plays an important role various fields such as medical diagnosis, crime prevention, web-based searching, and architecture. consists mainly of two stages: The first is extraction features second matching similarities. There several ways improv...

The revolutionary internet and digital technologies have imposed a need to have a system to organize abundantly available digital images for easy categorization and retrieval. The need to have a versatile and general purpose content based image retrieval (CBIR) system for a very large image database has attracted focus of many researchers of information-technology-giants and leading academic in...

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 ...

In this paper, we present the machine-controlled relevance feedback technique for the distributed contentbased image retrieval (CBIR) system. A nonlinear model based on the Gaussian-shaped radial basis function (RBF) is applied in the feedback process, and a bias weighting is introduced to the query content as the partial supervised function to improve the retrieval precision. This paper introd...

Content Based Image Retrieval (CBIR) system using Inter Space Local Binary Patterns (ISLBP) based features with high retrieval rate and less computational complexity is proposed in this paper. The property of LBP is it extracts the information based on distribution of edges in an image. This property made it a powerful tool for feature extraction of images in the data base. First the image is s...

Content-Based Image Retrieval (CBIR) is one of the most active hot spots in the current research field of multimedia retrieval. According to the description and extraction of visual content (feature) of the image, CBIR aims to find images that contain specified content (feature) in the image database. In this paper, several key technologies of CBIR, e. g. the extraction of the color and texture...

The term CBIR refers to the process of retrieving similar images from a large collection of image database. The image retrieval is done on the basis of similarity matching between query image and database images. Different feature extraction techniques are being used to extract features of an image. The important image features are Color, Texture, Shape, Spatial location, edges etc. The CBIR (C...