• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.46-54
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• 2006

Recently, the important of a personal identification is increasing according to expansion using each on-line commercial transaction and personal ID-card. Although a personal ID-card embedded RFID(Radio Frequency Identification) tag is gradually increased, the way for a person's identification is deficiency. So we need automatic methods. Because RFID tag is vary small storage capacity of memory, it needs effective feature extraction method to store personal biometrics information. We need new recognition method to compare each feature. In this paper, we studied the face verification system using Hippocampal neuron modeling algorithm which can remodel the hippocampal neuron as a principle of a man's brain in engineering, then it can learn the feature vector of the face images very fast. and construct the optimized feature each image. The system is composed of two parts mainly. One is feature extraction using NMF(Non-negative Matrix Factorization) and LDA(Linear Discriminants Analysis) mixture algorithm and the other is hippocampal neuron modeling and recognition simulation experiments confirm the each recognition rate, that are face changes, pose changes and low-level quality image. The results of experiments, we can compare a feature extraction and learning method proposed in this paper of any other methods, and we can confirm that the proposed method is superior to the existing method.

• The KIPS Transactions:PartB
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• v.15B no.1
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• pp.25-36
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• 2008

In this paper, we present a robust hand recognition approach to sudden illumination changes. The proposed approach constructs a background model with respect to hue and hue gradient in HSI color space and extracts a foreground hand region from an input image using the background subtraction method. Eighteen features are defined for a hand pose and multi-class SVM(Support Vector Machine) approach is applied to learn and classify hand poses based on eighteen features. The proposed approach robustly extracts the contour of a hand with variations in illumination by applying the hue gradient into the background subtraction. A hand pose is defined by two Eigen values which are normalized by the size of OBB(Object-Oriented Bounding Box), and sixteen feature values which represent the number of hand contour points included in each subrange of OBB. We compared the RGB-based background subtraction, hue-based background subtraction and the proposed approach with sudden illumination changes and proved the robustness of the proposed approach. In the experiment, we built a hand pose training model from 2,700 sample hand images of six subjects which represent nine numerical numbers from one to nine. Our implementation result shows 92.6% of successful recognition rate for 1,620 hand images with various lighting condition using the training model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.358-365
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• 2017

In this paper, we propose an object recognition method using image information to improve the efficiency of visual servoingfor industrial manipulators in industry. This is an image-processing method for real-time responses to an abnormal situation or to external environment change in a work object by utilizing camera-image information of an industrial manipulator. The object recognition method proposed in this paper uses the Otsu method, a thresholding technique based on separation of the V channel containing color information and the S channel, in which it is easy to separate the background from the HSV channel in order to improve the recognition rate of the existing Harris Corner algorithm. Through this study, when the work object is not placed in the correct position due to external factors or from being twisted,the position is calculated and provided to the industrial manipulator.

• The Journal of the Convergence on Culture Technology
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• v.4 no.4
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• pp.77-87
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• 2018

The study was a mixed design study that analyzed the effects of developing and applying a program to improve pregnancy recognition for severe low fertility. The study period was from April 1, 2018, to October 26, 2018, and the participants included 16 women of 19~21 age who lived in M City and M Gun. The process of program development is based on Dorothy Johnson 's theory of behavior system to induce change of perception, and reference literature review and national policy report. The program developed through the literature was finally developed by examining the experts panel discussion after deriving causes and alternatives for low fertility from 25 fertility women. The contents of program consist of three areas. Quantitative research results were analyzed using Shapiro Wilk and Wilcoxon sign rank using SPSS 18.0, and qualitative research results were analyzed using focus group. As a result of study, the perception of pregnancy increased significantly (P<0.01) with statistical significance as pre-experimental (M=3.21, SD=.342), post-experimental (M=4.46, SD=.398) and the result of content analysis appeared three themes as , , . In conclusion, the program was effective in improving the recognition of pregnancy for young women.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.31-39
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• 2018

Recently, there has been active studies to provide a user-friendly interface in a virtual reality environment by recognizing user hand gestures based on deep learning. However, most studies use separate sensors to obtain hand information or go through pre-process for efficient learning. It also fails to take into account changes in the external environment, such as changes in lighting or some of its hands being obscured. This paper proposes a hand gesture recognition method based on deep learning that is strong in external environments without the need for pre-process of RGB images obtained from general webcam. In this paper we improve the VGGNet and the GoogLeNet structures and compared the performance of each structure. The VGGNet and the GoogLeNet structures presented in this paper showed a recognition rate of 93.88% and 93.75%, respectively, based on data containing dim, partially obscured, or partially out-of-sight hand images. In terms of memory and speed, the GoogLeNet used about 3 times less memory than the VGGNet, and its processing speed was 10 times better. The results of this paper can be processed in real-time and used as a hand gesture interface in various areas such as games, education, and medical services in a virtual reality environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.365-368
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• 2021

In this study, a plastic bottle recycling bin system that utilizes an infrared sensor was implemented. The proposed system consists of a recognition unit, a control unit, an alarm unit, and a driving unit. The recognition unit detects the plastic bottle, measures the distance between the plastic bottle and the infrared sensor, extracts the value of the bottle, compares the extracted value with a standard range, and then transmits the control value to the control unit if the extracted value of the bottle is outside the standard range. In this case, the result of the presence or absence of a brand label or bottle cap is transmitted to the controller. The control unit opens the entrance of the recycling bin or alerts the alarm unit according to the result value transmitted from the sensor unit. In order to implement the proposed system, the recognition unit was implemented with an infrared sensor, and the control unit was made with an Arduino IDE controller, based on the C programming language. Additionally, the recognition unit and the control unit are able to communicate using analog signals. The proposed system accurately judges the presence or absence of a brand label and bottle cap of plastic bottles according to a predetermined algorithm. It then blocks the entrance of the recycling bin when a brand label or bottle cap is still attached. As the amount of waste discharged per person is relatively high and the majority of such waste is incinerated rather than recycled, the system proposed in this study is expected to increase the recycling rate of plastic bottles.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.530-536
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• 2020

The use of minutiae by fingerprint readers is robust against presentation attacks, but one weakness is that the mismatch rate is high. Therefore, minutiae tend to be used with skeleton images. There have been many studies on security vulnerabilities in the characteristics of minutiae, but vulnerability studies on the skeleton are weak, so this study attempts to analyze the vulnerability of presentation attacks against the skeleton. To this end, we propose a method based on the skeleton to recover the original fingerprint using a learning algorithm. The proposed method includes a new learning model, Pix2Pix, which adds a latent vector to the existing Pix2Pix model, thereby generating a natural fingerprint. In the experimental results, the original fingerprint is restored using the proposed machine learning, and then, the restored fingerprint is the input for the fingerprint reader in order to achieve a good recognition rate. Thus, this study verifies that fingerprint readers using the skeleton are vulnerable to presentation attacks. The approach presented in this paper is expected to be useful in a variety of applications concerning fingerprint restoration, video security, and biometrics.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.342-352
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• 2018

This study was conducted to evaluate the effects of physical activity practice rates and knowledge related to cardiocerebrovascular disease prevention on the health behavior of middle aged women. Data were collected from Oct to Nov 2017 from 142 middle-aged women living in 24 Eup, Myeon, and Dong areas in North Gyeongsangbuk-do Province using a structured questionnaire. The obtained data were analyzed using descriptive statistics, t-tests, ANOVA, Pearson's correlation, and stepwise multiple regression analysis. The major factors influencing health behavior were found to be alcohol consumption (${\beta}=0.15$, p=0.009), diet (${\beta}=0.16$, p=0.003), vigorous intensity (${\beta}=0.14$, p=0.011), marriage (${\beta}=0.19$, p<0.001), interest in one's own health (${\beta}=0.23$, p<0.001), and health recognition (ill: ${\beta}=0.31$, p<0.001). Alcohol consumption and diet were factors of cardiocerebrovascular knowledge, vigorous intensity was a factor of physical activity practice rate, marriage and interest in one's own health were factors of general characteristics, and health recognition was a factor in health-related characteristics. Health-promotion activity was positively correlated with knowledge regarding cardiocerebrovascular disease prevention (r=0.41, p<0.001) and physical activity practice rate (r=0.44, p<0.001). It will be necessary to develop and apply practical intervention programs based on disease prevention knowledge and physical activity to enhance the health behavior of middle aged women.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.226-235
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• 2020

This study was undertaken to investigate factors that affect the assessment of complications in diabetic eye and kidney diseases. Data was obtained from the National Community Health Survey, 2017. The subjects included were 25,829 respondents who had been diagnosed with diabetes. Logistic regression analysis was applied to determine the factors affecting associated diabetic eye disease (fundus examination) and kidney disease (microalbuminuria examination) complications. The diabetic eye disease complication rate was 35.6%, and diabetic kidney disease complication rate was 39.8%. Complications arising due to diabetes were determined to be 35.6% for eye diseases and 39.8% for kidney related diseases. Ed. Notes: The original sentence is not very lucid. I have suggested an alternate edit. I leave it to the author's discretion to accept or reject the same. Please delete whichever sentence is not suitable. Walking activity (OR=1.03, OR=1.02), hemoglobin A1c (HbA1c) recognition (OR=2.33, OR=2.33), blood glucose level recognition (OR=1.61, OR=1.71), diabetes drug therapy (OR=2.67, OR=3.05), and diabetic management education (OR=1.45, OR=1.47) were more likely to be evaluated for eye and kidney disease complications. Our results indicate that to increase the rate of screening for diabetic complications, it is necessary to develop a diabetes management system that includes the type and timing of diabetic complications, as well as different promotional methods that recognize HbA1C and blood glucose levels. Ed. Notes: Do you mean 'screening' methods? Please revise appropriately, if required. In addition, it is essential to develop a guideline for the management of diabetes mellitus, and to incorporate a screening test for diabetic complications in the national screening system.

• Journal of the Korean Society for Marine Environment & Energy
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• v.5 no.3
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• pp.28-34
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• 2002

As the technology of Speech Recognition(SR) and Text-To-Speech(TTS) develops rapidly, voice control and guidance system is thought to be very helpful for safe navigation. But Voice Control and Guidance System(VCGS) is not yet so popularly included in Navigation Supporting System(NSS). The main reason of this is that VCGS is so complicated and user-unfriendly that navigation officers hesitate to use VCGS. Frequent errors in operating VCGS due to low rate of SR are another reason. To make VCGS more practicable for safe navigation, we design the user-friendly VCGS. Firstly, by using interviews we survey functions and procedures that navigation officers want to be included in VCGS. Secondly, to raise the rate of SR, we tun the environmental noise in bridge and to reduce the errors due to low rate of SR in operating VCGS, we design the functions of self-correction. Also we apply a user-independent SR engine so that procedures of teaming of speakers is basically not necessary. Using simulator experiments the functions and procedures of the user-friendly YCGS for safe navigation are evaluated and the results of evaluation are fed back to the design. As a result, we can design the VCGS more helpful for safe navigation. In this paper, we describe the features of the user-friendly VCGS for safe navigation and discuss the results of simulator experiments.