Title: An adaptive computer-aided tongue diagnosis method using colour-calibration preprocessing and multiple feature synthesis based on Android platform

Authors: Miao Wang; Li Chen; Qing Li; Dongyi Wang; Yiqin Liu; Yi Zhang; Shoulan Bing; Huiliang Shang

Addresses: Research Lab for Construction and Application of Standards in Medical Informatics, Shanghai University of Traditional Chinese Medicine, Cailun Road, Shanghai, China ' Department of Electrical Engineering, Fudan University, No. 220 Handan Road, Yangpu District, Shanghai, China ' Department of Electrical Engineering, Fudan University, No. 220 Handan Road, Yangpu District, Shanghai, China ' Department of Electrical Engineering, Fudan University, No. 220 Handan Road, Yangpu District, Shanghai, China ' Department of Electrical Engineering, Fudan University, No. 220 Handan Road, Yangpu District, Shanghai, China ' School of Software, Fudan University, No. 220 Handan Road, Yangpu District, Shanghai, China ' Shanghai Research Institute of Acupuncture and Meridian, Shanghai, China ' Faculty of Department of Electrical Engineering, Fudan University, No. 220 Handan Road, Yangpu District, Shanghai, China

Abstract: Tongue diagnosis plays a significant role in Traditional Chinese Medicine. Owing to its experience-based nature, an increasing number of researchers have been studying on automatic tongue diagnosis methods. However, most methods fail to calibrate the input tongue images which rely on the quality of tongue images. In this paper, we present an optimised computer-aided tongue diagnosis method based on Android platform which makes up the drawbacks and insufficiency of our previous work. First, it calibrates the colour of the input tongue images and makes them standardised. Then the hue range of the brim pixels of the sample images is evaluated based on maximum likelihood estimate method. This can help us obtain edges and link them into a complete outline to finish tongue segmentation. Finally, we realise the new algorithm on Android platform which can give the classification of the tongue and make diagnosis. Compared to existing calibration algorithms, our system shows better robustness, comprehension and accuracy.

Keywords: colour calibration; feature extraction; tongue diagnosis; Android platform; computer-aided diagnosis; multiple features; feature synthesis; traditional Chinese medicine; tongue images; image quality; maximum likelihood estimation; MLE.

DOI: 10.1504/IJWMC.2015.073107

International Journal of Wireless and Mobile Computing, 2015 Vol.9 No.3, pp.240 - 249

Received: 16 Jun 2015
Accepted: 29 Jun 2015
Published online: 19 Nov 2015 *

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