A popular technique for retrieving images from huge and unlabeled image databases are content-based-image-retrieval (CBIR). However, the traditional information retrieval techniques do not satisfy users in terms of time consumption accuracy. Additionally, number accessible to growing due web development transmission networks. As result, digital creation occurs many places. Therefore, quick acce...

Researchers have recently focused their attention on Content-Based Image Retrieval (CBIR). It has emerged as one of the most fascinating areas in image processing and computer vision. With CBIR, comparable pictures that match query are pulled from an database. As a result, it necessitates feature extraction (Local / Global) similarity calculation. This paper uses CBIR technique to determine ima...

It is widely accepted that content-based image retrieval (CBIR) can be extremely useful for computer-aided diagnosis (CAD). However, CBIR has not been established in clinical practice yet. As a widely unattended gap of integration, a unified data concept for CBIR-based CAD results and reporting is lacking. Picture archiving and communication systems and the workflow of radiologists must be cons...

Content-based image retrieval (CBIR) has been heralded as a mechanism to cope with the increasingly larger volumes of information present in medical imaging repositories. However, generic, extensible CBIR frameworks that work natively with Picture Archive and Communication Systems (PACS) are scarce. In this article we propose a methodology for parametric CBIR based on similarity profiles. The a...

In this paper, a novel study on system profiles and adaptation of parameters for end-users of content-based indexing and retrieval (CBIR) applications are presented. The main objective of the study is improving the overall CBIR application performance in different hardware platforms having different technical capabilities and conditions. We define CBIR system profiles in terms of hardware and s...

Content-based image retrieval (CBIR) with global features is notoriously noisy, especially for image queries with low percentages of relevant images in a collection. Moreover, CBIR typically ranks the whole collection, which is inefficient for large databases. We experiment with a method for image retrieval from multimodal databases, which improves both the effectiveness and efficiency of tradi...

We describe the outcome of an effort to understand the behavior of content-based image retrieval (CBIR) technology by examining the behavior of a CBIR system in response to carefully constructed input query images. This work is preliminary and only considers a single CBIR system, SIMPLIcity[4]. We chose this particular system for expediency. It is our intention to develop a methodology suitable...

Content Based Image Retrieval (CBIR) systems based on shape using invariant image moments, viz., Moment Invariants (MI) and Zernike Moments (ZM) are available in the literature. MI and ZM are good at representing the shape features of an image. However, non-orthogonality of MI and poor reconstruction of ZM restrict their application in CBIR. Therefore, an efficient and orthogonal moment based C...

In Content-Based Image Retrieval (CBIR) systems, the visual contents of the images in the database are took out and represented by multi-dimensional characteristic vectors. A well known CBIR system that retrieves images by unsupervised method known as cluster based image retrieval system. For enhancing the performance and retrieval rate of CBIR system, we fuse the visual contents of an image. R...