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Sensors 2018, 18(9), 3051; https://doi.org/10.3390/s18093051

A Digital Shade-Matching Device for Dental Color Determination Using the Support Vector Machine Algorithm

1
Medical Device Development Center, Osong Medical Innovation Foundation, Cheongju, Chungbuk 361-951, Korea
2
Department of Electronics Engineering, Chungnam National University, Building E2, 79 Daehangno, Yuseong-gu, Daejeon 305-764, Korea
3
Department of Electronics Engineering, Kookmin University, 77 Jeongneung-no, Seongbuk-gu, Seoul 02707, Korea
These authors contributed equally to this work.
*
Authors to whom correspondence should be addressed.
Received: 27 July 2018 / Revised: 4 September 2018 / Accepted: 10 September 2018 / Published: 12 September 2018
(This article belongs to the Special Issue Machine Learning for Sensing and Healthcare)
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Abstract

In this study, we developed a digital shade-matching device for dental color determination using the support vector machine (SVM) algorithm. Shade-matching was performed using shade tabs. For the hardware, the typically used intraoral camera was modified to apply the cross-polarization scheme and block the light from outside, which can lead to shade-matching errors. For reliable experiments, a precise robot arm with ±0.1 mm position repeatability and a specially designed jig to fix the position of the VITA 3D-master (3D) shade tabs were used. For consistent color performance, color calibration was performed with five standard colors having color values as the mean color values of the five shade tabs of the 3D. By using the SVM algorithm, hyperplanes and support vectors for 3D shade tabs were obtained with a database organized using five developed devices. Subsequently, shade matching was performed by measuring 3D shade tabs, as opposed to real teeth, with three additional devices. On average, more than 90% matching accuracy and a less than 1% failure rate were achieved with all devices for 10 measurements. In addition, we compared the classification algorithm with other classification algorithms, such as logistic regression, random forest, and k-nearest neighbors, using the leave-pair-out cross-validation method to verify the classification performance of the SVM algorithm. Our proposed scheme can be an optimum solution for the quantitative measurement of tooth color with high accuracy. View Full-Text
Keywords: digital shade-matching device; dental color determination; support vector machine digital shade-matching device; dental color determination; support vector machine
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Kim, M.; Kim, B.; Park, B.; Lee, M.; Won, Y.; Kim, C.-Y.; Lee, S. A Digital Shade-Matching Device for Dental Color Determination Using the Support Vector Machine Algorithm. Sensors 2018, 18, 3051.

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