• Journal of Sasang Constitutional Medicine
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• v.19 no.3
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• pp.156-175
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• 2007

1. Objectives and Methods This study was performed to know the relationship between Sasang Constitution and characteristics of ordinary symptoms, inspection diagnosis of face and tongue. There were 666 participants(280 men and 386 women) who answered Sasang Constitutional Checkup list and were taken pictures of faces and tongues. Sasang Constitution was diagnosed by only PSSC(Phonetic System for Sasang Constitution). Distribution of Sasang Constitution and X2 test, kappa value for agreement were calculated using SPSS 10.0. 2. Results From characteristics of ordinary symptoms' point of view, Taeeumin had loud voices, big body shapes and easily sweated themselves. They felt good after sweating and had warm hands and feet. And their upper back, shoulders and chest were, they thought, well developed. They were apt to have meals quickly and overeat themselves. Soyangin and Soeumin had thin body shapes and were difficult to sweat themselves and felt powerless after sweating. They had cold hands and feet. Especially, Soeumin was apt to have meals slowly and a little amounts. They walked so fast. Soyangin was introvert and had developed their abdomen and waist. 'Looking heavy and steady' was higher in Taeeumin, 'delicate and modest' was higher in Soeumin(42.8%) and Soyangin(36.1 %) in first impression. It was thought to be difficult to discriminate Soyangin from Soeumin in first impression and make a notion of right Soyangin's first impression. Soyangin had pinky tongue color and little tongue fur whereas Soeumin had red tongue color and whitish tongue fur. Taeeumin had whitish tongue fur too. 3. Conclusions To diagnose Sasang Constitution much effectively, PSSC results and comprehensive Sasang Constitutional Checkup list extracted from effective Questionnaire items and Face and Tongue Inspection Diagnosis are thought to be needed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.1
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• pp.1-11
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• 1997

Austomated visual inspection(AVI) capability has become an important key component in the automated manufacturing system. In such a visual inspection system an intensity(or color) image of a scene is quickly affected by optical property of objects, condition and roughness of surface, lens and filters, image sensor property and lighting system. In particular, the lighting system disign is the most important factor, since it affects overall performance of the visual system. For fast and cheap automated visual inspection system it is important to obtain the good image quality which results from careful attention to the design of the lighting system. In this paper, the lighting subsystem of AVI system is analysed for the inspection of printed circuit board(PCB) patterns. The spectral reflectance of materials, which are composed of PCB, is measured for choosing the light source. The reflection property is theoretically obtained by a reflection model and also obtained by experiments which measure intensity with varying the viewing direction of image sensor and the lighting direction of illuminator. The illumination uniformity of a ring-type illuminator. The lighting system is designed based upon the experimental results and theoretial analysis.

• The Journal of Korean Medicine
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• v.20 no.2
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• pp.187-197
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• 1999

To assess the usefulness of tongue inspection for evaluating the Pattern identification in oriental medicine, we observed stroke patient's tongue and tongue coat and compared it with Pattern identification. The test group was composed of 85 acute stroke stage patients(within 72 hours of onset). Subjects were randomly selected from stroke patients admitted in the KyungHee University, Hospital of Oriental Medicine from December 1 1998 to June 30 1999. We took pictures of patient's tongue and tongue coat within 72hours from onset and checked Pattern identification at the same time. Tongues colored pale rose or red greatly outnumbered other colors. Tongue shape tended to be prickly or fissured, and tongue condition tended to be unflexible or deviated. Regarding tongue coat color, there were great amounts of yellow or clark yellow tongue coats, which were moist, thick or greasy in substance. The red tongue was significantly related to Fire-heat and deficiency of Yin syndrome, while faint white tongue to Damp syndrome(P=0.006). In terms of tongue coat, thin coat was related to Wind and Fire-heat syndromes, thick coat to Damp and Blood stasis syndrome, respectively (P=0.002). In conclusion, we thought that tongue inspection could be a useful Oriental medicine diagnosis in stroke.

• Korean Journal of Optics and Photonics
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• v.28 no.1
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• pp.1-8
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• 2017

A method for inspecting defects in display substrates utilizing Fourier optics is proposed in this paper. A cost-effective inspection system can be realized with the proposed method, because it does not require a high-magnification microscope. Also, the proposed method can avoid tight tolerance for variations in displacement between substrate and camera, which is stems from shallow depth of field of the high-magnification microscope. In addition, possible damage caused by collisions between substrate and the inspection equipment can be avoided. The decision algorithm can be simpler than for a conventional inspection system, because spatial shift of periodic substrate patterns does not affect the intensity distribution of the diffracted light, by the Fourier transform property. The proposed method is explained with numerical studies, and experiments are carried out to check its feasibility for color-filter substrates of a liquid-crystal display.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.463-465
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• 2021

Currently, the inspection method printed on food packages and boxes is to sample only a few products and inspect them with human eyes. Such a sampling inspection has the limitation that only a small number of products can be inspected. Therefore, accurate inspection using a camera is required. This paper proposes a deep learning object recognition technology model, which is an artificial intelligence technology, as a method for detecting the defects of expiration date printed on the product packaging. Using the Faster R-CNN (region convolution neural network) model, the color images, converted gray images, and converted binary images of the printed expiration date are trained and then tested, and each detection rates are compared. The detection performance of expiration date printed on the package by the proposed method showed the same detection performance as that of conventional vision-based inspection system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1079-1082
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• 2005

This paper deals with the algorithm development that inspects defects such as Lens Focus, Focus check, Black Defect, Dark Defect, Dim Defect, Color Defect, and Line Defect, Angle Defect, IrisAgc Defect caused by the process of 2M Class Compact Camera Module (CCM). Domestic market was majorly comprised of VGA(0.3 million pixel) market. But in the middle of year 2004, camera phone with Mega Pixel has appeared, and it is estimated that the camera phone with Mega Pixel will take up to 28% of total phone sales if it is released in the end of year 2004. Since the inspection of finished products is done manually, it is major obstacle in production increment In this paper, to solve these problems, we developed the imaging processing algorithm to inspect the defects in captured image of assembled CCM. The performances of the developed inspection system and we can recognize various types of defect of CCM modules with good accuracy and high speed

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.8
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• pp.710-718
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• 2000

In this paper we described an approach to automation of visual inspection of solder joint defects of SMC(Surface Mounted Components) on PCBs(Printed Circuit Board) by using neural network and fuzzy rule-based classification method. Inherently the surface of the solder joints is curved tiny and specular reflective it induces difficulty of taking good image of the solder joints. And the shape of the solder joints tends to greatly vary with the soldering condition and the shapes are not identical to each other even though the solder joints belong to a set of the same soldering quality. This problem makes it difficult to classify the solder joints according to their qualities. Neural network and fuzzy rule-based classification method is proposed to effi-ciently make human-like classification criteria of the solder joint shapes. The performance of the proposed approach is tested on numerous samples of commercial computer PCB boards and compared with the results of the human inspector performance and the conventional Kohonen network.

• Journal of the Korean Society of Safety
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• v.32 no.6
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• pp.98-103
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• 2017

In Korea, the guideline for the bridge safety inspection requests to assess surface degradation, including crack, efflorescence, spalling, and so on, for the rating of concrete bridges. Currently, the assessment of efflorescence is performed based on the visual inspection of expertized engineers, which may result in subjective inspection result. In this study, a novel method using a hyperspectral camera is proposed for objective and accurate assessment of concrete efflorescence. The hyperspectral camera acquires the light intensity for a number of continuous spectral bands of light for each pixel in an image, which makes the hyperspectral imaging technique provides more detailed information than a color camera that collects intensity for only three bands corresponding to RGB (red, green, and blue) colors. A stepwise assessment algorithm is proposed based on the spectral features to decompose efflorescence area from the inspected concrete area. The algorithm is tested in the laboratory test using two concrete specimens, one of which is dark colored with efflorescence on a surface while the other is bright concrete without efflorescence. The test shows high accuracy and applicability of the proposed efflorescence assessment using a hyperspectral camera.

• The Journal of the Korea Contents Association
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• v.6 no.4
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• pp.69-80
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• 2006

Interest about baby health increased into promise of all life health on society. Prevention disease or treatment about baby health is important, but it is important that first of grasping baby state through correct diagnosis. In this paper, diagnosis method for baby ocular inspection of Oriental medicine applying image processing technology is presented. For this, extracting baby frontal face image based on skin color, five sensory organs extraction and extraction of myeongdang based on position information is proposed. Finally, usefulness of method Proposed by an experiment world prove.

• Journal of Korea Multimedia Society
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• v.13 no.2
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• pp.196-204
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• 2010

In this paper, we develope a defect inspection method for each buttons of keypad of cellular phones before they are assembled. The proposed algorithm consists of the similar color checking and its classification, font error detection, and scratch detection based on the segmentation of keypad area and font, translation and rotation processing sequentially. Especially, the proposed segmentation method approximate the pad region as B-spline function to deal with illumination change due to the shape of key button with the slant and curved surface followed by simple thresholding. And also, the rotational information is obtained by using eigen value and eigen vector very fast and effectively. The experimental results show that the performance of the proposed algorithm is good when it is applied to in-line process.