• Journal of Korea Multimedia Society
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• v.7 no.11
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• pp.1531-1539
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• 2004

In this paper, we propose an efficient method for locating human lips. Based on Point Distribution Model and Principle Component Analysis, a lip shape model is built. Lip boundary model is represented based on the concatenated gray level distribution model. We calculate the distribution of shape parameters using Gaussian mixture. The problem to locate lip is simplified as the minimization problem of matching object function. The Down Hill Simplex Algorithm is used for the minimization with Gaussian Mixture for setting initial condition and refining estimate of lip shape parameter, which can refrain iteration from converging to local minima. The experiments have been performed for many images, and show very encouraging result.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.11
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• pp.2051-2057
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• 2007

In Oriental medicine, the status of a tongue is the important indicator to diagnose one's health like physiological and clinicopathological changes of inner parts of the body. The method of tongue diagnosis is not only convenient but also non-invasive and widely used in Oriental medicine. However, tongue diagnosis is affected by examination circumstances a lot like a light source, patient's posture and doctor's condition. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, segmenting a tongue is inevitable but difficult since the colors of a tongue, lips and skin in a mouth are similar. The proposed method includes preprocessing, graph-based over-segmentation, detecting positions with a local minimum over shading, detecting edge with color difference and estimating edge geometry from the probable structure of a tongue, where preprocessing performs down-sampling to reduce computation time, histogram equalization and edge enhancement. A tongue was segmented from a face image with a tongue from a digital tongue diagnosis system by the proposed method. According to three oriental medical doctors' evaluation, it produced the segmented region to include effective information and exclude a non-tongue region. It can be used to make an objective and standardized diagnosis.

• Journal of Korea Multimedia Society
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• v.4 no.5
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• pp.396-405
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• 2001

Usually it is difficult to extract facial regions in a complex image by using only a predetermined skin color. Expecially, it is more difficult to separate them from background regions that contains the skin color. This paper proposes a face detection method by using gradual range expansion of an initial skin color. By analyzing the skin color distribution several images that are collected in the Web, the range of dense distribution is selected as the range of the initial skin color. In each expanding step, expanded regions in the image are tested whether they can be actual facial regions by using the information of the shape of general face and the location of face organs. The shape of general face is modeled as an ellipse and the aspect ratio of its bounding box is used to define the shape constraint for faces. Only the eyes and lips are used as the face organs, which can be easily detected by extracting horizontal edges in the expanded regions. through several experiments, it is confirmed that the proposed method can detect exactly not only faces having partly distorted regions by highlight but also faces neighboring similar color regions.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.167-174
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• 2013

TIn this paper, we find the face in color images and the ability to track the face was implemented. Face tracking is the work to find face regions in the image using the functions of the computer system and this function is a necessary for the robot. But such as extracting skin color in the image face tracking can not be performed. Because face in image varies according to the condition such as light conditions, facial expressions condition. In this paper, we use the skin color pixel extraction function added lighting compensation function and the entire processing system was implemented, include performing finding the features of eyes, nose, mouth are confirmed as face. Lighting compensation function is a adjusted sine function and although the result is not suitable for human vision, the function showed about 4% improvement. Face features are detected by amplifying, reducing the value and make a comparison between the represented image. The eye and nose position, lips are detected. Face tracking efficiency was good.

• The Journal of the Acoustical Society of Korea
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• v.22 no.5
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• pp.375-382
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• 2003

Lip-reading technique based on bimodal is to enhance speech recognition rate in noisy environment. It is most important to detect the correct lip-image. But it is hard to estimate stable performance in dynamic environment, because of many factors to deteriorate Lip-reading's performance. There are illumination change, speaker's pronunciation habit, versatility of lips shape and rotation or size change of lips etc. In this paper, we propose the IIR filtering in time-domain for the stable performance. It is very proper to remove the noise of speech, to enhance performance of recognition by digital filtering in time domain. While the lip-reading technique in whole lip image makes data massive, the Principal Component Analysis of pre-process allows to reduce the data quantify by detection of feature without loss of image information. For the observation performance of speech recognition using only image information, we made an experiment on recognition after choosing 22 words in available car service. We used Hidden Markov Model by speech recognition algorithm to compare this words' recognition performance. As a result, while the recognition rate of lip-reading using PCA is 64%, Time-domain filter applied to lip-reading enhances recognition rate of 72.4%.

• Analytical Science and Technology
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• v.26 no.4
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• pp.235-244
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• 2013

Detection of halogens using laser-induced breakdown spectroscopy (LIBS) in open air is very difficult since their strong atomic emission lines are located in VUV region. In NIR region, there are other emission lines of halogens through electronic transitions between excited states. However, these lines undergo Stark broadening severely. We report the observation of the emission lines of halogens in laser-induced plasma (LIP) spectra in NIR region using a helium gas flow. Particularly, the emission lines of iodine at 804.374 and 905.833 nm from LIPs have been observed for the first time. In the helium ambient gas, Stark broadening of the emission lines and background continuum emission could be suppressed significantly. Variations of the line intensity, plasma temperature, and electron density with the helium flow rate was investigated. Detection of chlorine and bromine in flame retardant of rubbers was demonstrated using this method. Finally, we suggest a pulsed helium gas jet as a practical and ecomonical helium gas source for the LIBS analysis of halogens in open air.

• Journal of Oral Medicine and Pain
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• v.36 no.2
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• pp.91-97
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• 2011

Helicobacter pylori (H. pylori) is bacterial infection, with more than half of the world population infected and relates to many oral disease such oral lichen planus, recurrent aphthous ulceration, periodontal disease and halitosis and so on. Burning mouth syndrome(BMS) is defined as a burning sensation of the oral mucosa, lips, and/or tongue, in the absence of specific oral lesions. The etiology of BMS is suggested local, systemic and psychological factors and researchs related BMS and to infection of H. pyloir in the oral cavity are few. The purpose of this study was to evaluate relationship between burning mouth syndrome and H. pylori in the oral cavity. We recruited 21 subjects with burning mouth syndrome and 21 subjects as control group. Samples in the oral cavity were taken area of buccal mucosa, dorsum of the tongue and saliva. We analysed samples by nested polymerase chain reaction(PCR). The results were as follows: 1. Among 21 patients with burning mouth sydrome and 21 subjects of control group, 6(29%) and 3(14%) were positive respectively(P>0.05). 2. In detection rate of H. pylori in area taken sample, 3(14%), 2(10%) and 4(19%) were positive in buccal mucosa, dorsum of the tongue and saliva of patient and 2(10%) and 1(5%) were positive in dorsum of the tongue and saliva of control group(P>0.05). Conclusively, we can guess that H. pylori in the oral cavity is not related with burning mouth syndrome.