Title: A new algorithm for medical images indexing based on wavelet transform and principal component analysis

Authors: Souad Meziane Tani; Ismail Boukli Hacene; Abdelhafid Bessaid

Addresses: Department of Computer Science, Faculty of Science, University of Tlemcen, Tlemcen 13000, Algeria ' Department of Biomedical Engineering, Technology Faculty, University of Tlemcen, Tlemcen 13000, Algeria ' Department of Biomedical Engineering, Technology Faculty, University of Tlemcen, Tlemcen 13000, Algeria

Abstract: Medical equipment technologies produce a vast number of images that are stored in large databases; efficient indexing algorithms are required to access these databases. This paper proposes a novel hybrid algorithm for medical image indexing. The hybridisation of wavelet transform based on lifting scheme and principal component analysis has been used in some image processing area but they have not been used for image indexing. Wavelet transform is used to decompose images, then principal component analysis method is applied to extract pertinent components. The extracted features are used to create image signature. Finally, image is retrieved by comparing the signatures of query image and all images databases using Euclidean distance. We haves tested our algorithm on the retinal image, cerebral and melanoma databases. The results obtained by our algorithm are compared with several published methods cited in the literature and shows an efficiency of 95%, which is significantly higher than recent methods in CBIR domain.

Keywords: CBIR; content-based image retrieval; melanoma databases; texture; PCA; lifting; feature extraction; retinal images; cerebral databases; Euclidean distance; wavelet transform; medical images; image indexing; principal component analysis.

DOI: 10.1504/IJBET.2016.079143

International Journal of Biomedical Engineering and Technology, 2016 Vol.22 No.2, pp.126 - 136

Received: 15 Apr 2015
Accepted: 11 Jan 2016
Published online: 14 Sep 2016 *

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