Image Retrieval

3064 Words7 Pages

I. INTRODUCTION
Digital images are composed of pixels. Each pixel represents the colour at a single point of the image. Rectangular array of pixels are called as a bitmap or a digital image. Advance development of image procurement and storage technology have lead to marvellous development in very huge and detailed image databases [1]. A massive volume of image data such as digital photographs, medical images and satellite images are generated every day [2].
Image mining can automatically extract meaningful information from a huge of image data are increasingly in demand. It is an interdisciplinary venture that essentially draws upon expertise in artificial intelligence, computer vision, content based image retrieval, database, data mining, digital image processing and machine learning. Image mining frameworks [3] are grouped into two broad categories: function-driven and information-driven. The problem of image mining combines the areas of content-based image retrieval, data mining, image understanding and databases. Image mining techniques include image retrieval, image classification, image clustering, image segmentation, object recognition and association rule mining.
Image Retrieval is performed by matching the features of a query image with those in the image database. The collection of images in the web are growing larger and becoming more diverse. Retrieving images from such large collections is a challenging problem. The research communities study about image retrieval from different angles, one being text-based and the other visual-based. The text-based Image retrieval applies traditional text retrieval techniques to image annotations. The content-based Image retrieval apply image processing techniques to first extract image features and then retrieve relevant images based on the match of these features.
The rest of this paper is organized as follows. Section 2 discusses about the related work of image retrieval. Section 3 and 4 gives a text and content based image retrieval. Section 5 discussed the conclusion.

II. RELATED WORK
Digital images are currently widely used in medicine, fashion, architecture, face recognition, finger print recognition and bio-metrics etc. Recently, Digital image collections are rapidly increased very huge level. That image contains a huge amount of information. Conversely, we cannot make it information as useful unless it is organized so as to allow efficient browsing, searching, and retrieval.
Image retrieval has been a very dynamic research area. two major research communities such as database management and computer vision has study image retrieval from different angles, one being text-based and the other content-based. Late 1970s, the text-based image retrieval can be traced back.

Open Document