An efficient image processing methodology based on fuzzy decision for dental shade matching

Issue title: The 6th International Multi-Conference on Engineering and Technology Innovation 2017 (IMETI2017)

Guest editors: Wen-Hsiang Hsieh

Article type: Research Article

Authors: Lin, Ting-Lan^a | Chuang, Chien-Hui^b | Chen, Shih-Lun^{b; *} | Lin, Nung-Hsiang^c | Miaou, Shaou-Gang^b | Lin, Szu-Yin^d | Chen, Chiung-An^e | Liu, Hui-Wen^b | Villaverde, Jocelyn Flores^f

Affiliations: [a] Department of Electronic Engineering, National Taipei University of Technology, Taiwan, ROC | [b] Department of Electronic Engineering, Chung Yuan Christian University, Taiwan, ROC | [c] Department of General Dentistry, Chang Gang Memorial Hospital, Taiwan, ROC | [d] Department of Information Management, Chung Yuan Christian University, Taiwan, ROC | [e] Department of Electrical Engineering, Ming Chi University of Technology, Taiwan, ROC | [f] School of EECE, Mapua University, Manila, Philippines

Correspondence: [*] Corresponding author. Shih-Lun Chen, Department of Electronic Engineering, Chung Yuan Christian University, Taoyuan City 320, Taiwan, ROC. E-mail: [email protected]

Abstract:  For dentists, it is very important to determine the color of the denture. Shade selection in dental practice is an important and difficult task. In the dental shade matching process, the shade selection will be affected by the observer’s physiological conditions such as age, mood, fatigue, and so on. These will make a difference on the judgement between the matching shade and the actual teeth color. In the past, dentists use shade tabs as a reference basis to match the teeth in the intra-oral environment. In this paper, an efficient color analysis methodology based on image processing and fuzzy decision techniques is proposed for dental shade matching. Since the color information is a very important index for the shade matching, the proposed methodology used the chrominance values Cb and Cr to increase the accuracy of color analysis. In order to improve the performance of the proposed methodology, three formulas, such as PSNR value of Cb, PSNR value of Cr, and S-CIELAB value, were selected by a fuzzy decision model. As shown in the results, the proposed efficient methodology based on fuzzy decision techniques improved at least 1.92 % in average accuracy and 0.59 in average score from the PSNR (Cb) and PSNR (Cr) in this work. In addition, the average values of the accuracies and scores in this work are 92.31% and 98.74, respectively, which are much better than the previous studies. To summarized, this work is the first study that applied fuzzy decision with the PSNR (Cb), PSNR (Cr) and S-CLIELAB information for dental shade matching. The results showed that the proposed methodology performs better than the previous work and other methods.

Keywords: Dental shade matching, fuzzy decision, chrominance, Cb, Cr, PSNR (Peak Signal-to-Noise Ratio), S-CLIELAB

DOI: 10.3233/JIFS-169887

Journal: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1133-1142, 2019