Unified technique for colour image retrieval based on orthogonal polynomial model and multiresolution features. (2nd July 2016)

• Record Type: Journal Article
• Authors: Kamarasan, M.
• Is Part Of: International journal of image and data fusion. Volume 7:Number 3(2016)
• Page Start: 243
• Page End: 263
• Publication Date: 2016-07-02
• Subjects: optimum level -- Bhattacharrya distance -- CBIR -- orthogonal polynomial -- multiresolution -- wavelet transform -- Gaussian distribution; Image processing -- Periodicals; Multisensor data fusion -- Periodicals; Multisensor data fusion; Periodicals; 621.36705
• DOI: 10.1080/19479832.2015.1046955
• Languages: English
• ISSNs: 1947-9832

Abstract

Abstract : This paper proposes wavelet-based orthogonal polynomial model for content-based image retrieval. The wavelet coefficients are categorised into low-frequency and high-frequency based on criteria. The criteria are adaptively determined and fixed according to the nature and structure of the image, because the wavelet-based orthogonal polynomial model spatially localises the frequency information of image. Wavelet technique is employed to derive a multiresolution pyramid structure. Features such as spectrum of energy and spatial relation among the pixels are extracted at optimum level that helps in the formation of a feature vector. The Bhattacharyya distance and orthogonal cosine similarity method is employed to find the distance value between the feature vectors of the query and target images. The proposed method is simple and suitable for fast response requirements since the features extracted at the optimum-level image contain only fewer dominant wavelet coefficients. The efficiency of the proposed feature vector is experimented with standard image databases. Also, the proposed system is compared with the other existing methods.