ISSN: 2319-9873 RRJET | Vol 2 | Issue 1 | Jan – March, 2013 11 Research and Reviews: Journal of Engineering and Technology Combination of Radon and Hue Composite Features for Retrieval of Shapes Tohid Sedghi* Department of Electrical Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran Article Received: 01/01/2013 Revised: 04/02/2013 Accepted: 07/02/2013 *For Correspondence Department of Electrical Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran Keywords: Shape Classification, Descriptor, Retrieval, Radon Transform, LDA. ABSTRACT This paper proposes a simple Shape-Based Retrieval (SBR) systems, which a novel feature-based shapes descriptors using Radon composite features by using statistical and spectral analysis are used in this system, Instead of analyzing shapes directly in the spatial domain. SBR systems employ Texture as primary feature with shape secondary features. Till now systems exploit spatial features. None of the available systems combines all features, texture, and shape for retrieval. Moreover relatively few systems use Radon Transform in texture extraction features, despite the widely acclaimed efficiency. The proposed system uses combination of integrated first and second moments of radon transformed image features, and Hue Moments features of the regions as shape features then Linear Discriminated Analysis (LDA) are applied for decreasing the dimension of feature vector and non linear combination of vector dimensions for generating optimum features. Experiments demonstrate that proposed novel feature-based shapes system provides a higher degree of retrieval and are compared with several state-of-the-art approaches. INTRODUCTION A retrieval system is a system for searching and retrieving images from a large database of digital images. The most common method of image retrieval utilize some method of annotation such as keywords, or descriptions to the images so that retrieval can be performed over the labels. Unfortunately manual annotation is time consuming, laborious and expensive. Shape based retrieval (SBR) describes the process of retrieving desired images from the image database on the basis of syntactical image features. Research comprise of systems such as [1,2,3] . The features most often used include texture, shape information and multi-resolution pixel intensity transformations such as wavelets or multi-scale Gaussian filtering [4] and in old and traditional systems low level features extraction method are used in this method always semantic gap are sensed so, for eliminating semantic gap combinational features such as textural and shape features are used simultaneously and for increasing the percentage of retrieval some nonlinear and linear feature and vector dimension are evaluated. The organization of this paper as follows: In Section II, we provide a brief review of Radon transform equations. Section III gives the Feature Extraction. In Section IV, the retrieval strategy is introduced, and the results of the experiments and extensive comparisons are performed with several state-of-the-art algorithms. Conclusions are drawn in Section V. Radon Transform over view An image is represented by a function s(x,y), and the image can be determined by a set of projections along lines taken at different angles. Therefore, the Radon transform is defined as: dxdy y x y x s R s           ) sin cos ( ) , ( ) , (       (1) Where     , 0  , and      ,  .  .  represents the Dirac delta-function