IRMA-Improvisation of image retrieval with Markov chain based on annotation

Abstract

A large collection of images is referred to as image database. An image database is a system where image data are integrated, coupled and stored. Image data include the raw images, image set and information derived from images by automated or computer assisted image analysis. In a small collection of images, simple browsing can identify an image. In text-based retrieval, images are retrieved using keywords, like subject, headings, or classification codes, which in turn are used as retrieval keys during search and retrieval of images. Usually, the only way of searching these collections of images was by keyword indexing, or simply by browsing. Text-based retrieval is non-standardized for the image extraction because different users employ different keywords for annotation. Text-based image retrieval uses traditional database techniques to manage images like giving keyword or by searching the required images from the local database. In this paper retrieval of image from database by giving a similar image is performed by the spatial database property of the image.