• Fire Science and Engineering
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• v.19 no.4 s.60
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• pp.64-68
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• 2005

In this paper, we studied fire position recognition and alarm system when we acquired CCDcamera image of fire region and position. We proposed effectively extraction system of boundary of fire region using RED Filtering, and applied 2-graylevel image method to fire boundary extraction. Finally we can make system of fire position and region using mask extraction and matching for fire recognition. For the purpose of experiment result, we effectively recognized that the tire occurrence position and region have steadily spread.

• Proceedings of the KSPS conference
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• 2004.05a
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• pp.231-234
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• 2004

This paper describes an efficient method for improving the noise-robustness in speech recognition in a running car by considering wind noise. In driving car, mainly three kind of noises engine noise, tire noise and wind noise, are severely affect recognition performance. Especially wind noise is an important factor in driving car with window opened. We analyzed wind noise in various driving conditions that are 60, 80, 100 km/h with window fully opened, window half opened. We clarified that the recognition rate is significantly degenerated when the wind noise components in the frequency range above 200 Hz are large. We developed a preprocessing method to improve the noise robustness despite of wind noise. We adaptively changed the cutoff frequency of the front-end high-pass filter from 100 through 200 Hz according to the level of the wind noise components. By this method, the recognition rate is considerably improved for all kind of driving conditions

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.79-84
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• 2019

Video image based technology is being used in various fields with continuous development. The demand for vision system technology that analyzes and discriminates image objects acquired through cameras is rapidly increasing. Image processing is one of the core technologies of vision systems, and is used for defect inspection in the semiconductor manufacturing field, object recognition inspection such as the number of tire surfaces and symbols. In addition, research into license plate recognition is ongoing, and it is necessary to recognize objects quickly and accurately. In this paper, propose a recognition model through the rotational alignment of objects after checking the angle value of the tilt of the object in the input video image for the recognition of inclined objects such as numbers or symbols marked on the surface. The proposed model can perform object recognition of the rotationally sorted image after extracting the object region and calculating the angle of the object based on the contour algorithm. The proposed model extracts the object region based on the contour algorithm, calculates the angle of the object, and then performs object recognition on the rotationally aligned image. In future research, it is necessary to study template matching through machine learning.

• The Journal of the Korea Contents Association
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• v.1 no.1
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• pp.8-14
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• 2001

In this paper, we suggests a algorithms of recognizing the disease region by extracting particular organ from medical image. This method can extract liver region in spite of input image including many organs and charged format by using multi-threshold of feed-back-structure for segmentation liver region, and suggest the recognition of disease region in extracted liver, using multi-neural network structured by RBF and BP, overcoming the defect of single-neural network. The algorithm in this paper is proficient in adaptation for a multi form change of input medical image. This algorithm can be used at tole-medicine through automatic recognition after recognizing of the disease region by real-tire medical Image.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.93-96
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• 2001

In this paper, we present a vision algorithm and method for input image improvement and preprocessing of dented and raised characters on the sidewall of tires. we define optical condition between reflect coefficient and reflectance by the physical vector calculate. On the contrary this work will recognize the engraved characters using the computer vision technique. Tire input images have all most same grey levels between the characters and backgrounds. The reflectance is little from a tire surface. therefore, it's very difficult segment the characters from the background. Moreover, one side of the character string is raised and the other is dented. So, the captured images are varied with the angle of camera and illumination. For optimum input images, the angle between camera and illumination was found out to be with in 90。 .In addition, We used complex filtering with low-pass and high-pass band filters to improve input images, for clear input images. Finally we define equation reflect coefficient and reflectance. By doing this, we obtained good images of tires for pattern recognition.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.125-132
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• 2012

In this paper, We proposes FE-SM/SONN for recognizing blurred and smeared skid mark image caused by sudden braking of a vehicle. In a blurred and smeared skid marks, tread pattern image is ambiguous. To improve recognition of such image, FE-SM/SONN reads skid marks utilizing Fuzzy Logic and distinguishing tread pattern SONN(Self Organization Neural Networks) recognizer. In order to substantiate this finding, 48 tire models and 144 skid marks were compared and overall recognition ratio was 89%. This study showed 13.51% improved recognition compared to existing back propagation recognizer, and 8.78% improvement than FE-MCBP. The expected effect of this research is achieving recognition of ambiguous images by extracting distinguishing features, and the finding concludes that even when tread pattern image is in grey scale, Fuzzy Logic enables the tread pattern recognizable.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.9-14
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• 2018

The vision system is a device for acquiring images and analyzing and discriminating inspection areas. Demand for use in the automation process has increased, and the introduction of a vision-based inspection system has emerged as a very important issue. These vision systems are used for everyday life and used as inspection equipment in production processes. Image processing technology is actively being studied. However, there is little research on the area definition for extracting objects such as character recognition or semiconductor packages. In this paper, define a region of interest and perform edge extraction to prevent the user from judging noise as an edge. We propose a noise-robust alignment correction model that can extract the edge of a region to be inspected using the distribution of edges in a specific region even if noise exists in the image. Through the proposed model, it is expected that the product production efficiency will be improved if it is applied to production field such as character recognition of tire or inspection of semiconductor packages.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.1
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• pp.124-132
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• 2002

In this paper, we present a vision algorithm and method for input image improvement and preprocessing of dented and raised characters on the sidewall of tires. we define optical condition between reflect coefficient and reflectance by the physical vector calculate. On the contrary this work will recognize the engraved characters using the computer vision technique. Tire input images have all most same grey levels between the characters and backgrounds. The reflectance is little from a tire surface. therefore, it's very difficult segment the characters from the background. Moreover, one side of the character string is raised and the other is dented. So, the captured images are varied with the angle of camera and illumination. For optimum Input images, the angle between camera and illumination was found out to be with in 90$^{\circ}$. In addition, We used complex filtering with low-pass and high-pass band filters to improve input images, for clear input images. Finally we define equation reflect coefficient and reflectance. By doing this, we obtained good images of tires for pattern recognition.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.535-538
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• 2002

Machine vision algorithms, which are composed of noise elimination algorithm, crack detection and mapping algorithm, and path planning algorithm, are required for sealing crack networks effectively and automation of crack sealing.. Noise elimination algorithm is the first step so that computer take cognizance of cracks effectively. Noises should be removed because common road includes a lot of noises(mark of oil, tire, traffic lane, and sealed crack) that make it difficult the computer to acknowledge cracks accurately. The objective of this paper is to propose noise elimination algorithm, prove the efficiency of the algorithm through coding. The result of the coding is represented in this paper as well.

• Journal of the Korean Home Economics Association
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• v.43 no.7 s.209
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• pp.67-77
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• 2005

The purpose of this study was to survey the concern for nutrition and the degree of nutritional knowledge of elementary school children's parents and their perception on the eating habits of their children. This study also investigated the effects of the concern for nutrition and the nutritional knowledge on the eating habits of their children. The questionnaire was answered by 383 mothers and fathers in the Kyonggi area. The general nutritional attitude and the perception of their children's eating habits were represented by frequencies and analyzed tv chi-square test, and Fisher's exact test. The difference of nutritional knowledge was represented tv mean and S.D. and was analyzed by one-way ANOVA test. Statistical significance was tested at the 0.05 level. The main results of the study are summarized as follows. 1) Parents had a comparatively deep concern for nutrition and a high level of knowledge. With increasing concern for nutrition, nutritional knowledge tended to be better and the higher proportion of participation in the nutritional education program increased. 2) The majority$(58.5\%)$ of the subjects thought that the eating habit of their children was not appropriate. The subjects had relatively high recognition about their children's eating habits and pointed out the unbalanced diet, snacks, and skipping a meal among their children's eating habits. Nevertheless, there were no significantly differences among the concern for nutrition of the parents and perception on their children's eating habits. As the parents' nutritional attitude, concern for nutrition, and nutritional knowledge can affect the children's eating habits, tire suggest that schools open nutritional education programs for parents in order to acquire proper food and nutrition information, and that schools and homes should be more closely connected.