• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.759-764
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• 2005

In this paper we describe a face recognition using EBGM(Elastic Bunch Graph Matching) method. Usally, the PCA and LDA based face recognition method with the low-dimensional subspace representation use holistic image of faces, but this study uses local features such as a set of convolution coefficients for Gabor kernels of different orientations and frequencies at fiducial points including the eyes, nose and mouth. At pre-recognition step, all images are represented with same size face graphs and they are used to recognize a face comparing with each similarity for all images. The proposed algorithm has less computation time due to simplified face graph than conventional EBGM method and the fuzzy matching method for calculating the similarity of face graphs renders more face recognition results.

• Journal of Korean Tunnelling and Underground Space Association
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• v.9 no.1
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• pp.83-89
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• 2007

As tunnel excavation generats stress release, a stability security of tunnel face is mainly important in case of tunnel excavation in the weak grounds. Using the steel bar or glass fiber pipe which had regular hardness, a face bolt method to reinforce previously is applied to an excavation object tunnel face aspect among measures methods regarding this. Therefore, used $FLAC^{3D}$ Ver. 2.1 on 5 Case of 0.5D (2EA), 1.0D, 1.5D, 2.0D with the length and 6 Case of 0, 20, 40, 60, 80, 100EA with the number of the bolt that a face bolt method was installed at these papers in the necessary weak grounds in order to review applicability of the tunnel face reinforcement method that used these face bolts, and executed three dimension continuous analysis.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.93-104
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• 2023

In modern society, the service method is tended to prefer the non-face-to-face method rather than the face-to-face method. However, services that recommend products such as shoes will inevitably be face-to-face method. In this paper, for the purpose of non-face-to-face service, a system that a foot size is automatically measured and some shoes are recommended based on the measurement result is proposed. To analyze the performance of the proposed method, size measurement error rate and recommendation performance were analyzed. In the recommendation performance experiments, a total of 10 methods for similarity calculation were used and the recommendation method with the best performance among them was applied to the system. From the experiments, the error rate the foot size was small and the recommendation performance was possible to derive significant results. The proposed method is at the laboratory level and needs to be expanded and applied to the real environment. Also, the recommendation method considering design could be needed in the future work.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.1006-1009
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• 2003

In this paper, we propose a technique of the recognition of partial face. Most of the research is concentrated on the recognition of whole face Since part of the face area in an image can be damaged or overlapped, face recognition based on partial face is required. PCA and LDA technique is applied to the recognition of partial face. Also, a new method to combine the results of the recognition of parts of the face.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.804-813
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• 2021

The purpose of this study was on the learning satisfaction of dental hygiene students according to the face-to-face and non-face-to-face teaching methods in the COVID-19 educational environment. A self-reported questionnaire was completed by 122 dental hygiene students of G University located in Gwangju from October to November, 2020. The general characteristics, instructional characteristics, teaching methods, and learning satisfaction were investigated, and the collected data were analyzed using SPSS 18.0. The effective practical teaching method chosen by the students was face-to-face, and there was a significant difference according to the class choice. The learning satisfaction according to the general characteristics showed a significant difference in the preferred practice method for improving instrument technique. The face-to-face classes showed significantly higher learning satisfaction in terms of checking on doing well study during class and the convenience. In addition, as a result of analyzing the factors influencing learning satisfaction, the choice of face-to-face class was confirmed as a significant variable. Therefore, in order to increase the learning satisfaction of students, it is necessary to design a class that essentially includes face-to-face class when planning a practice class.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.120-121
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• 2006

In this paper, We have designed a face recognition system based on the embedded Linux. This paper has an aim in embedded system to recognize the face more exactly. At first, the contrast of the face image is adjusted with lightening compensation method, the skin and lip color is founded based on YCbCr values from the compensated image. To take advantage of the method based on feature and appearance, these methods are applied to the eyes which has the most highly recognition rate of all the part of the human face. For eyes detecting, which is the most important component of the face recognition, we calculate the horizontal gradient of the face image and the maximum value. This part of the face is resized for fitting the eye image. The image, which is resized for fit to the eye image stored to be compared, is extracted to be the feature vectors using the continuous wavelet transform and these vectors are decided to be whether the same person or not with PNN, to miminize the error rate, the accuracy is analyzed due to the rotation or movement of the face. Also last part of this paper we represent many cases to prove the algorithm contains the feature vector extraction and accuracy of the comparison method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5605-5623
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• 2016

We propose a face recognition method that utilizes the LCP face descriptor. The proposed method applies a LoG mask to extract a face contour response, and employs the LCP algorithm to produce a binary pattern representation that ensures high recognition performance even under the changes in illumination, noise, and aging. The proposed LCP algorithm produces excellent noise reduction and efficiency in removing unnecessary information from the face by extracting a face contour response using the LoG mask, whose behavior is similar to the human eye. Majority of reported algorithms search for face contour response information. On the other hand, our proposed LCP algorithm produces results expressing major facial information by applying the threshold to the search area with only 8 bits. However, the LCP algorithm produces results that express major facial information with only 8-bits by applying a threshold value to the search area. Therefore, compared to previous approaches, the LCP algorithm maintains a consistent accuracy under varying circumstances, and produces a high face recognition rate with a relatively small feature vector. The test results indicate that the LCP algorithm produces a higher facial recognition rate than the rate of human visual's recognition capability, and outperforms the existing methods.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.213-220
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• 2023

Face recognition is a very important process in video monitoring and is a type of biometric technology. It is mainly used for identification and security purposes, such as ID cards, licenses, and passports. The recognition process has many variables and is complex, so development has been slow. In this paper, we proposed a face recognition method using CNN, which has been re-examined due to the recent development of computers and algorithms, and compared with the feature comparison method, which is an existing face recognition algorithm, to verify performance. The proposed face search method is divided into a face region extraction step and a learning step. For learning, face images were standardized to 50×50 pixels, and learning was conducted while minimizing unnecessary nodes. In this paper, convolution and polling-based techniques, which are one of the deep learning technologies, were used for learning, and 1,000 face images were randomly selected from among 7,000 images of Caltech, and as a result of inspection, the final recognition rate was 98%.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.289-297
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• 2022

The purpose of this study was to investigate the perception of dental students based on their experiences of online classes after taking non-face-to-face education courses for all the school semesters in 2020. For the research method, an online survey was conducted on A survey was conducted on 161 dental students enrolled in A University. The analytical method was conducted through frequency analysis, correlation analysis, and multiple regression analysis. The survey analysis findings showed that the satisfaction of dental students' about the non-face-to-face education course was above 4.2, and the detailed items were in the order of the appropriateness of the attendance processing method, satisfaction with recorded video lectures, and the assessment method of the course grade. In the case of the factors that affect the satisfaction of non-face-to-face education courses, the learning system and assessment method were statistically significant. The online class type that is most preferred by the students is recorded video lectures, and the highest number of participants chose 21~30 minutes as the appropriate time for the class content. It is considered that the application of the online system will continue to be used together with face-to-face education courses in the education site and various university-level efforts like systematic support are required to achieve effective learning achievements. This study only investigated the non-face-to-face education operation conditions of A University, so it cannot be generalized to all universities, but it can be used as basic data to provide education curriculum design and supportive measures for the compatibility of face-to-face and non-face-to-face courses.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.117-119
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• 2006

In this work, we suggest another method to localize DFT in spatial domain. This enables DFT algorithm to be used for local pattern matching. Once calculated, it costs same load to calculate localized DFT regardless of the size or the position of local region In spatial domain. We applied this method to face detection problem and got the results which prove the utility of our method.