Intelligent Image Retrieval Techniques: A Survey

Abstract

In the current era of digital communication, the use of digital images has increased for expressing, sharing and interpreting information. While working with digital images, quite often it is necessary to search for a specific image for a particular situation based on the visual contents of the image. This task looks easy if you are dealing with tens of images but it gets more difficult when the number of images goes from tens to hundreds and thousands, and the same contentbased searching task becomes extremely complex when the number of images is in the millions. To deal with the situation, some intelligent way of content-based searching is required to fulfill the searching request with right visual contents in a reasonable amount of time. There are some really smart techniques proposed by researchers for efficient and robust content-based image retrieval. In this research, the aim is to highlight the efforts of researchers who conducted some brilliant work and to provide a proof of concept for intelligent content-based image retrieval techniques.

Applying metric space and pivot-based indexing on combined features of bio-images for fast execution of composite queries

“…In Content Based Image Retrieval, there are two methodologies for recovery from the database, the primary approach manages recovery through explanations that is metadata, which depicts the picture and the second approach utilizes the picture question itself for the seeking reason [1]. The keyword based retrieval faces semantic gap, and in many cases fails to retrieve the relevant information.…”

Image Retrieval using High Order Local Autocorrelation and MFCM

“…Another method for speaking to any picture is by processing the interior components either via robotized strategy or by semi-mechanized procedure. In many fields of picture recovery robotized investigation ascertains a few insights which can further be utilized as a part of the request to figure the related substance highlights [1]. In spite of the fact that such calculations give required outcomes and a fulfilment level in many fields has been accomplished, yet a solitary system that fits best in a wide range of client's necessities is still to be created.…”

“…Hence, the entryways are as yet open to create new systems as per the necessities of image recovery applications [1] [2]. The necessity of client for the most part relies on upon the unique situation and the application situation instead of the coordinating catchphrases as it were.…”

Multidimensional Markov Stationary Feature for Image Retrival Systems

“…With the proliferation of the world-wide-web, and the rapid increase of the multimedia data such as image and video, there is a strong demand for developing efficient techniques for storing, browsing, retrieval and indexing to exploit the full benefit of the explosive growth [1][2][3][4]. In content-based image retrieval system, images from database are automatically indexed by summarizing their low level visual contents such as color, texture, shape or spatial relationship according to user's visual requirement.…”