RATIONALE AND OBJECTIVES The aim of this study was to investigate whether using a fractal dimension as an objective index (quantitative measure) to assess and control the "visual" or "texture" similarity of reference-image regions selected by a content-based image retrieval (CBIR) scheme would (or would not) affect the performance of the scheme in classification between image regions depicting ...

Objective: The objective of this study is to conduct a comprehensive review existing research and literature in the field Content-Based Image Retrieval (CBIR). This highlights key challenges associated with extraction representation visual semantics images. paper discusses measure used computing similarity ranking retrieved images by CBIR system. limitation traditional approaches also current d...

In this study, an interactive Content-Based Image Retrieval (CBIR) system that allows searching and retrieving images from databases is designed and developed. Based on the fuzzy c-means clustering algorithm, the CBIR system fuses color and texture features in image segmentation. A technique to form compound queries based on the combined features of different images is devised. This technique a...

Pseudo-relevance feedback is a common technique in information retrieval. Content Based Information Retrieval systems (CBIR), like visual retrieval engines, suffer from low performance due to the distance between the semantic interpretation of an image and its visual features. This is the reason why such a systems are empowered when textual information is associated to the images in the collect...

Content Based Image Retrieval (CBIR) system is an emerging research area in effective digital data management and retrieval paradigm. In this article, a novel CBIR system based on a new Multiscale Geometric Analysis (MGA)-tool, called Ripplet Transform Type-I (RT) is presented. To improve the retrieval result and to reduce the computational complexity, the proposed scheme utilizes a Neural Netw...

Content based image retrieval systems (CBIR) have drawn wide attention in recent years due to the exponential growth of multimedia information storage in various fields of life. Given a query image, the goal of CBIR system is to retrieve content related images from databases by employing suitable image matching algorithms. Many algorithms have been proposed in the past for image matching. This ...

Content-based image retrieval (CBIR) is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases. The term "content" in this context might refer to colors, shapes, textures, or any other information that can be derived from the image itself. CBIR has been used to describe the process of retrieving desir...

In this paper, a growing hierarchical self-organizing quadtree map (GHSOQM) is proposed and used for a content-based image retrieval (CBIR) system. The incorporation of GHSOQM in a CBIR system organizes images in a hierarchical structure. The retrieval time by GHSOQM is less than that by using direct image comparison using a flat structure. Furthermore, the ability of incremental learning enabl...

Content-based image retrieval (CBIR) has been one the most vivid research areas in the field of computer vision, and substantial progress has been made over the last years. As such, many have argued for the use of CBIR to support medical imaging diagnosis. However, the sheer volume of data produced in radiology centers has precluded the use of CBIR in the daily routine of hospitals and clinics....