• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.861-864
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• 2014

본 논문은 혀 미각 영역별 분석을 통해 신체의 이상 여부에 대한 정보를 제공하는 설진 진단 시스템의 첫 단계로 얼굴 영상에서 혀 영역을 검출하는 실험을 통하여 미각 영역별 분석의 기반을 다진다. 제안하는 알고리즘은 혀 영상을 획득한 후, Haar-like Feature를 이용하여 혀를 검출한다. 검출된 혀 영역은 HSV컬러모델의 특징을 이용하여 이진화 한 후, Connected Component Labeling을 이용하여 혀 영역 분리한다. 한방병원의 환자들의 혀 사진 100장을 이용하여 90%의 검출률을 확인하였다.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.10 no.2
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• pp.141-146
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• 2016

In this paper, we apply limited area mask operation and active contour model to accurately detect tongue area outline in tongue diagnosis system. To accurately analyze the properties of the tongue, first, the tongue area to be detected. Therefore an effective segmentation method for detecting the edge of tongue is very important. It experimented with tongue image DB consists of 20~30 students 30 people. Experiments on real tongue image show the good performance of this method. Experimental results show that the proposed method extracts object boundaries more accurately than existing methods without mask operation.

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.374-377
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• 2012

본 논문은 다양한 조명환경에서의 실시간 설진 진단을 위한 혀 영역 검출 및 영역 분할 방법을 제안한다. 임의의 환경에서 얻어낸 이미지에서 혀 영역의 추출과 추출된 영역에서의 혀의 상태를 진단하는 데는 많은 어려움이 있다. 다양한 조명환경에서의 영상으로부터 혀 영역을 추출하기 위하여 본 논문에서는 ASM을 이용한다. 검출된 영역을 6개의 영역으로 영역 분할한 다음 HSV영상으로 변환하고 색상 정보를 분석함으로써 신체의 건강상태를 판별하는 방법을 제한한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.801-804
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• 2013

We propose a new tongue examination model according to the taste division of tongue. The proposed sytem consists of image acquisition, region segmentation, color distribution analysis and abnormality decision of tongue. Tongue DB which is classified into abnormality is constructed with tongue images captured from oriental medicine hospital inpatients. We divided 4 basic taste(bitter, sweet, salty and sour) regions and performed color distribution analysis targeting each region under HSI(Hue Saturation Intensity) color model. To minimize the influence of illumination, the histograms of H and S components only except I are utilized. The abnormality of taste regions each by comparing the proposed diagnosis model with diagnosis results by a doctor of oriental medicine. We confirmed the 87.5% of classification results of abnormality by proposed algorithm is coincide with the doctor's results.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.271-273
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• 2023

불수의적인 혀 움직임과 떨림은 다른 신체 부위의 떨림증상이 없이 혀만 움직이는 증상을 말하며, 신경 정신과적 문제와 한의학의 기혈허약 등의 증상에 의해 발생할 수 있다. 혀 영상 촬영 장치로 정면과 측면의 혀를 연속을 촬영하여 혀의 움직임과 떨림을 탐색하려 한다. 혀의 표면은 코너와 같은 특징점을 구하기 어려운 모양이므로 혀의 움직임의 특성을 찾아내는 것은 매우 어려운 일이다. 움직임을 추적하는 방법 중에서 Farnebäck optical flow 방법은 모든 픽셀에 대해서 optical flow를 계산하여 혀의 움직임을 추적할 수 있었다. 이러한 움직임의 크기를 정면과 측면 영상에 대해서 구할 수 있었고, 움직임의 방향도 구할 수 있었다. 혀의 움직임과 떨림에 대한 위치별 정보와 세기 정보를 이용하여 건강상태를 진단할 수 있을 것으로 생각된다.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.3
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• pp.96-101
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• 2015

A tongue coating evaluation method for WTCI(Winkel Tongue Coating Index) is proposed in this paper, which is used as the diagnostic criteria in the tongue diagnosis. This method uses the color channel analysis and tongue coating extraction from the ultraviolet tongue image. Proposed method analyzes the histogram distribution of the respective color channel for extracting a tongue coating, and performs the verification test from the selected color channel in the tongue coating extraction. Also, Objectivity of the tongue diagnostic criteria is verified by the artificial sample and real-tongue image experiments. In order to evaluate the performance of the proposed Computerized Assistant WTCI Evaluation method, after verifying a measurement accuracy by using the artificial sample images, and applying to the various real-tongue image of subjects. As a result, the proposed WTCI method is very successful.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.4
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• pp.826-832
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• 2016

In this paper, we propose a tongue diagnosis system for determining the presence of specific taste crack area as a first step in the digital tongue diagnosis system that anyone can use easily without special equipment and expensive digital tongue diagnosis equipment. Training DB was developed by the Haar-like feature, Adaboost learning on the basis of 261 pictures which was collected in Oriental medicine. Tongue candidate regions were detected from the input image by the learning results and calculated the average value of the HUE component to separate only the tongue area in the detected candidate regions. A tongue area is separated through the Connected Component Labeling from the contour of tongue detected. The palate regions were divided by the relative width and height of the tongue regions separated. Image on the taste area is converted to gray image and binarized with each of the average brightness values. A crack in the presence or absence was determined via Connected Component Labeling with binary images.

• Journal of the Korea Society of Computer and Information
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• v.18 no.4
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• pp.45-55
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• 2013

In this study, we propose a tongue diagnosis system which detects the tongue from face image and divides the tongue area into six areas, and finally generates tongue fur ratio of each area. To detect the tongue area from face image, we use ASM as one of the active shape models. Detected tongue area is divided into six areas and the distribution of tongue coating of six areas is examined by SVM. For SVM, we use a 3-dimensional vector calculated by PCA from a 12-dimensional vector consisting of RGB, HSV, Lab, and Luv. As a result, we stably detected the tongue area using ASM. Furthermore, we recognized that PCA and SVM helped to raise the ratio of tongue coating detection.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.253-256
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• 2011

본 논문은 기존의 디지털 설진 시스템이 아닌 임베디드 환경에서의 실시간 설진 진단 방법을 제안한다. 임의의 환경에서 얻어낸 이미지에서 혀 영역의 추출과 추출된 영역에서의 혀의 상태를 진단하는데는 많은 어려움이 있다. 다양한 조명환경에서의 영상으로부터 혀 영역을 추출해 내는 방법으로는 ASM을 이용하는 방법이 있는데 이는 검출률이 낮아 정확도가 떨어진다. 이를 보완하기 위해 본 논문에서는 ASM과 물체 외곽 정보 복원에 기반을 둔 컬러 분산 스테이크 기법을 사용하여 정확도를 개선하는 방법을 제안한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.73-76
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• 2013

This paper proposes a tongue and its direction recognition algorithm which compares and estimates pixel distribution in the mouth area. As the size of smart phones grows, facial gesture control technology for a smart phone is required. Firstly, the nose area is detected and the mouth area is detected based on the ratio of the nose to mouth. After detecting the mouth area, it is divided by a pattern of grid and the distribution of pixels having the similar color to the tongue is tested for each segment. The recognition rate was nearly 80% in the experiments performed with five researchers among our laboratory members.