Combination of Radon and Hue Composite Features for Retrieval of Shapes
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.