• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1601-1607
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• 2009

Vision system is an object recognition system analyzing image information captured through camera. Vision system can be applied to various fields, and automobile types recognition is one of them. There have been many research about algorithm of automobile types recognition. But have complex calculation processing. so they need long processing time. In this paper, we designed vision box based on embedded system. and suggested automobile types recognition system using the vision box. As a result of pretesting, this system achieves 100% rate of recognition at the optimal condition. But when condition is changed by lighting and angle, recognition is available but pattern score is lowered. Also, it is observed that the proposed system satisfy the criteria of processing time and recognition rate in industrial field.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.29-40
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• 2012

A challenging research issue that has been one of growing importance to those working in human-computer interaction are to endow a machine with an emotional intelligence. Thus, emotion recognition technology plays an important role in the research area of human-computer interaction, and it allows a more natural and more human-like communication between human and computer. In this paper, we propose the multimodal emotion recognition system using face and speech to improve recognition performance. The distance measurement of the face-based emotion recognition is calculated by 2D-PCA of MCS-LBP image and nearest neighbor classifier, and also the likelihood measurement is obtained by Gaussian mixture model algorithm based on pitch and mel-frequency cepstral coefficient features in speech-based emotion recognition. The individual matching scores obtained from face and speech are combined using a weighted-summation operation, and the fused-score is utilized to classify the human emotion. Through experimental results, the proposed method exhibits improved recognition accuracy of about 11.25% to 19.75% when compared to the most uni-modal approach. From these results, we confirmed that the proposed approach achieved a significant performance improvement and the proposed method was very effective.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.31-40
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• 2012

Face recognition refers to the process of identifying individuals based on their facial features. It has recently become one of the most popular research areas in the fields of computer vision, machine learning, and pattern recognition because it spans numerous consumer applications, such as access control, surveillance, security, credit-card verification, and criminal identification. However, illumination variation on face generally cause performance degradation of face recognition systems under practical environments. Thus, this paper proposes an novel face recognition system using a fusion approach based on local binary pattern and two-dimensional principal component analysis. To minimize illumination effects, the face image undergoes the local binary pattern operation, and the resultant image are divided into two sub-images. Then, two-dimensional principal component analysis algorithm is separately applied to each sub-images. The individual scores obtained from two sub-images are integrated using a weighted-summation rule, and the fused-score is utilized to classify the unknown user. The performance evaluation of the proposed system was performed using the Yale B database and CMU-PIE database, and the proposed method shows the better recognition results in comparison with existing face recognition techniques.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.299-307
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• 2013

The aim of this paper is the improvement of identification performance and the reduction of computational quantities in the face recognition system based on SIFT-Grid. Firstly, we propose a composition method of integrated template by removing similar SIFT keypoints and blending different keypoints in variety training images of one face class. The integrated template is made up of computation of similarity matrix and threshold-based histogram from keypoints in a same sub-region which divided by applying SIFT-Grid of training images. Secondly, we propose a computation method of similarity for identify of test image from composed integrated templates efficiently. The computation of similarity is performed that a test image to compare one-on-one with the integrated template of each face class. Then, a similarity score and a threshold-voting score calculates according to each sub-region. In the experimental results of face recognition tasks, the proposed methods is founded to be more accurate than both two other methods based on SIFT-Grid, also the computational quantities are reduce.

• Korean Journal of Occupational Health Nursing
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• v.10 no.1
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• pp.55-65
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• 2001

The purpose of this study was to find out the status of occupational health management and the degree of recognition about the occupational health management of employees 248 small-scale enterprises which have been managed by the small-scale enterprises health care management support institution in 1999, were selected for study, in Kwang-Ju City. 98 employees were selected in 116 industries of them to grasp recognition of employees about the occupational health management. ► The Status of Occupational Health Management 1. Of the sample industries, 62.1 percent employed eleven to twenty-nine workers. Of the sample workers, 72.1 percent occupied workers who were engaged in the production line. 2. Environment evaluation was made on 82.7 percent of the sample industries and general exam made on 66.5 percent and specific health exam done on 73.4 percent. 3. The harmful factors in the sample industries were found to lie noise, dust, solvent, heavy metal, etc. 4. In general health exam 1,774 workers were participated and 148 workers got the result of above grade C and were diagnosed as having the problems with digestive system (63.6%), circulatory system(20.6%). etc. ► The Degree of Recognition about The Occupational Health Management of Employees. 1. Respondents were mainly in the twenties (42.9%), males(69.1%), duration of working period of five to ten years(24.0%), office workers(51.0%), monthly income under one million(55.7%). 2. Recognition of employees about the occupational health management consists of workplace environmental evaluation, health education, health exam and protector management. Their recognition on health education showed high score (mean 3.1), but generally the score was low(mean 2.9).

• Journal of Korean Academy of Fundamentals of Nursing
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• v.11 no.1
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• pp.31-40
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• 2004

Purpose: The purpose of this study was to describe nurses' recognition of, and practice level in management of general nosocomial infections, and methicillin resistant staphylococcus aureus (MRSA) and vancomycin resistant enterococci (VRE) infections. Method: A self-administered questionnaire was used to collect data. Data were collected on June, 2003 from 190 nurses in one university affiliated hospital located in Suwon. Result: The mean score for nurses' recognition of general nosocomial infection control was 3.57, MRSA control was 3.54, and VRE control was 3.86. The mean score on practice for control of general nosocomial infection was 3.19, for MRSA control, 3.20, and for VRE control, 3.63. There were statistically significant relationships between the recognition level and practice level for general nosocomial, MRSA, and VRE infection control. According to the general characteristics of the nurses, the mean scores for both recognition and practice were higher for those nurses who had had infection control education, for those who had worked longer in nursing, and for those who worked in the ICU. Conclusion: It is suggested that appropriate hospital infection control programs should be developed through continuous education and practice to improve nurses' level of the practice in general infection control, and especially in MRSA and VRE infection control.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.69-77
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• 2021

This paper deals with the development of an application that converts the PDF music score entered by the user into a MIDI file of the chord the user wants. This application converts the PDF file into a PNG file for chord conversion when the user enters the PDF music score file and the chord which the user wants to change. After recognizing the melody of sheet music through image processing algorithm and recognizing the tempo of sheet music notes through deep learning, then the MIDI file of chord for existing sheet music is produced. The OpenCV algorithm and deep learning can recognize minim note, quarter note, eighth note, semi-quaver note, half rest, eighth rest, quarter rest, semi-quaver rest, successive notes and chord notes. The experiment shows that the note recognition rate of the music score was 100% and the tempo recognition rate was 90% or more.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.20 no.1
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• pp.17-22
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• 2009

Objectives : A higher level of aggression has been reported for children with attention-deficit/hyperactivity disorder (ADHD) than for non-ADHD children. Aggression was shown to have a negative effect on the social functioning of children with ADHD. The ability to recognize facial emotion expression has also been related to aggression. In this study, we examined whether impulsivity and dysfunctional recognition of facial emotion expression could explain the aggressiveness of children with ADHD. Methods : 67 children with ADHD participated in this study. We measured the ability to recognize facial emotion expression by using the Emotion Recognition Test (ERT) and we measured aggression by the T score of the aggression subscale of the Child Behavior Checklist (CBCL). Impulsivity was measured by the ADHD diagnostic system (ADS). Results : The teacher rated level of aggression was related to the score of recognizing negative affect. After controlling for the effect of impulsivity, this relationship is not significant. Only the score of the visual commission errors ex plained the level of aggression of children with ADHD. Conclusion : Impulsivity seems to have a major role in explaining the aggression of children with ADHD. The clinical implication of this study is that effective intervention for controlling impulsivity may be expected to reduce the aggression of children with ADHD.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.8 no.3
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• pp.151-160
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• 2014

In this study, the effect of the automotive haptic-seat technology which can transmit the driving information by the vibro-stimulus from the seat was investigated to overcome previous system's limitation relied on the visual and audial method and to help handicap driving. A prototype haptic seat cover with 30 coin-type motors and driver module were developed for this sake. In an experiment of seat vibration stimulation being performed under virtual driving situation by targeting the elderly aged over 65 years old, average score of test subjects for total vibration recognition was 3.5/4 points and recognition rate of 87.5% was represented. In addition, a result that all the test subjects totally recognized overspeed warning signal of 4 times was represented. As a result of statistical analysis for vibration recognition score by each group depending on TMT score, a significant difference was not found and a result that tactile function of which vibration is recognized even by the aged whose visual, perceptional function is declined showed an equal ability was obtained.. In this study it was shown that the seat vibration stimulus could be used to transfer the old drivers' information while driving.

• Journal of the Korea Convergence Society
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• v.11 no.6
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• pp.1-6
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• 2020

In this study, research on character recognition, which is one of the fields of computer vision, was conducted. Optical character recognition, which is one of the most widely used character recognition techniques, suffers from decreasing recognition rate if the recognition target deviates from a certain standard and format. Hence, this study aimed to address this limitation by applying deep learning techniques to character recognition. In addition, as most character recognition studies have been limited to English or number recognition, the recognition range has been expanded through additional data training on Korean text. As a result, this study derived a deep learning-based character recognition algorithm for Korean text recognition. The algorithm obtained a score of 0.841 on the 1-NED evaluation method, which is a similar result to that of English recognition. Further, based on the analysis of the results, major issues with Korean text recognition and possible future study tasks are introduced.