• Proceedings of the KAIS Fall Conference
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• 2008.11a
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• pp.287-289
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• 2008

본 논문은 개인의 혀영상을 이용한 건강 모니터링 방법을 제안한다. 이 방법은 혀의 절대적 특징들을 이용하지 않고, 병원에서 검진된 기준 건강 상태(reference health condition)와의 차이인 상대적 특징들을 사용한다. 사용자는 건강 모니터링 시스템으로 매일 혀영상을 촬영하여 전통 중의학에 기반한 관심영역을 추출하고 분석하도록 한다. 실험에서 1개월간 제안한 방법으로 혀영상들을 분석한 결과 본 논문의 방법이 건강 모니터링에 사용될 수 있음을 보였다.

• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.533-534
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• 2011

본 논문에서 적외선(IR; Infrared), 자외선(UV; Ultraviolet), 가시광선(VR; Visible ray)의 영역에서 촬영한 설진 영상으로부터 가장 효과적인 설태 인식을 위한 최적 혀 영상 분석 방법을 제안한다. 제안한 방법은 설진에서 혀 영상 촬영을 위한 최적 파장 범위와 해당 파장에서 설태 분석에 최적의 컬러 영상을 선정한다. 최적 영상 선정을 위해서는 각 파장별로 촬영한 혀 영상을 LAB, HSV, YcBcR, RGB 컬러모델로 변환하고, 변환된 영상들로부터 설태와 비설태 영역의 히스토그램(Histogram)을 분석에 의해서 영역-분별력을 측정한다. 실험 결과 설진에서 설태 인식을 위한 최적 혀 영상은 자외선 영역에서의 RGB 컬러모델로 나타났다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1219-1223
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• 2006

Tongue is one of the most important parts in patient diagnosis in traditional Korean(Chinese) medicine. This paper presents health monitoring method using tongue images of a person. The method uses not absolute tongue features but relative ones which are differences from reference health condition(RHC), diagnosed in hospital, for a person. A user can give tongue images to a health monitoring system everyday, which extracts regions of interest (ROI's) of the tongue, and compares their features with reference health condition. In the experiments, tongue image analysis for a person by our computerized method encouraged us that the method using tongue images can be contributed for health monitoring.

• 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.

• 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.

• 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.

• 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.

• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.4
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• pp.125-131
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• 2016

Tongue image segmentation is critical for automation of the tongue diagnosis system. However, most image segmentation methods for tongue diagnosis systems in oriental medicine have been proposed as user-based manual types or semi-automatic types. This study proposed a new method for tongue image segmentation, which is the most important image processing stage for complete automation of the tongue diagnosis system in oriental medicine. The proposed method improved the conventional snake algorithm, by making improvement on the internal energy function so that, as the points move outward reversely, the snake energy function is minimized, by using the image characteristics of tongue images. To calculate external energy, hierarchical spatial filtering is applied to ensure resistance against noise. Also, The proposed method was tested by using sample images and actual images, and showed more robustness against the background noise than the conventional snake algorithm. And, when one selected point was moved by the improved snake algorithm, energy values at the starting, middle, and end points were analyzed, and showed robustness that does not fall in the local minima.