ISSN(Online): 2320-9801 ISSN (Print): 2320-9798 International Journal of Innovative Research in Computer and Communication Engineering (An ISO 3297: 2007 Certified Organization) Vol. 3, Issue 1, January 2015 Copyright to IJIRCCE 10.15680/ijircce.2015.0301066 508 A Survey on Feature Based Image Retrieval Using Classification and Relevance Feedback Techniques Keyuri M. Zinzuvadia 1 , Prof. Bhavesh A. Tanawala 2 , Prof. Keyur N.Brahmbhatt 3 PG Student, Department of Computer Engineering, B.V.M. Engineering College, V. V. Nagar, India 1 Assistant Professor, Department of Computer Engineering, B.V.M. Engineering College, V. V. Nagar, India 2 Assistant Professor, Department of Information Technology, B.V.M. Engineering College, V. V. Nagar, India 3 ABSTRACT: Now a day, digital world increase with bandwidth, handheld devices, storage technologies and social networking sites and huge volume of images are stored on web. With significantly huge image database it is difficult to mine that data and retrieve relevant images. Feature Based Image Retrieval is a very important research area in the field of image processing. It is comprises of low level feature extraction such as color, texture and shape and similarity measures for the comparison of images. Recently, the research focus in FBIR has been in reducing the semantic gap, between the low level visual features and the high level image semantics. Here in this paper we have provided comparative study of various methods which are available for each step of FBIR system. In Proposed system architecture HSV space histogram will be used for colour information extraction. Gabor filter will be use for texture feature extraction and shape feature will be extract using moment invariant method. In this study multiple feature extraction will be use by combining above three methods. Based on the extracted feature Support vector machine classification technique is applied. Here classification reduce the search space and reduce retrieval time. After that for given relevant images relevance feedback algorithm is applied which provide user intension for resultant images to the system .This increase classification accuracy by taking feedback from user which decrease semantic gap. KEYWORDS: FBIR, Feature Extraction, color, texture, shape, Classification technique I. INTRODUCTION In our digital world, multimedia data plays a vital role in every field such as e-commerce, entertainment, education, medicine, aerospace and so on. With the increasing use of internet and handheld devises there is an enormous volume of digital images are generated every day .This all useful information extract properly if it is efficiently stored, indexed accurately , easily search and retrieved .Image mining deals with image retrieval ,indexing and storing. This is combination image processing and data mining techniques. The increased bandwidth availability to access the internet in the will allow the users to search for and browse through video and image databases located at remote sites [6]. Therefore, fast and accurate retrieval of images from large databases is an important problem that needs to be addressed. Feature Based Image Retrieval (FBIR) or content based image retrieval is the retrieval of images based on their visual features such as color, texture and shape.The ultimate goal of a FBIR system is to avoid the use of textual descriptions for an image by the user. This kind of a textual-based image retrieval system always suffers from two problems: high- priced manual annotation and inaccurate and inconsistent automated annotation. On the other hand, the cost associated with manual annotation is prohibitive with regards to a large-scale data set [4].As a result fbir which extract visual content of images like color , shape, texture, edge, layout and the desired images are retrieved from a large collection of images on the basis of features that can be automatically extracted.