Content-Based Image Retrieval Features: A Survey

Features in Content-based Image Retrieval Systems: a Survey

This article provides a framework to describe and compare content-based image retrieval systems. Sixteen contemporary systems are described in detail, in terms of the following technical aspects: querying, relevance feedback, result presentation, features, and matching. For a total of 44 systems we list the features that are used. Of these systems, 35 use any kind of color features, 28 use text...

Content Based Image Retrieval: Survey

The requirement for development of CBIR is enhanced due to tremendous growth in volume of images as well as the widespread application in multiple fields. Texture, color, shape and spatial layout are the underlying traits to represent and index the images. These peculiar features of images are extracted and implemented for a similarity check among images. The problem of content based image retr...

A Survey: Content Based Image Retrieval

-------------------------------------------------------ABSTRACT----------------------------------------------------------The field of image processing is addressed significantly by the role of CBIR. Peculiar query is the main feature on which the image retrieval of content based problems is dependent. Relevant information is required for the submission of sketches or drawing and similar type of...

Content-Based Image Retrieval Systems: A Survey

Content-Based Image Retrieval Systems: A Survey

In many areas of commerce, government, academia, and hospitals, large collections of digital images are being created. Many of these collections are the product of digitizing existing collections of analogue photographs, diagrams, drawings, paintings, and prints. Usually, the only way of searching these collections was by keyword indexing, or simply by browsing. Digital images databases however...