• Journal of Fashion Business
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• v.8 no.1
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• pp.76-90
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• 2004

The purpose of this study was to classify women's face types and to analyze the measurement of face types. For study, 180 adult women(aged between 20 and 29) in Pusan and Ulsan area was sampled to be measured for facial types. Data were analyzed by Frequencies, Means, Duncan's Multiple Range Test, Distinction analysis. The major results were as followed. Women's face types were classified by 6 types and there were round shape(29.4%), oblong shape(18.9%), inverted triangle shape(16.1%), square shape(13.9%), egg shape(11.7%), diamond shape(10.0%) in the subject. Phyiognomic facial height was 182.38mm, the upper face length was 59.82mm, the middle face length 60.82mm, the lower face length 61.76mm, and the index of face length to face breadth was 1.35. The face width was 134.90mm, interocular distance 34.75mm, the nose width 33.93mm, and mouth width was 43.87mm. And also, differences from those measurements like forehead breadth, face length/bizygion breadth, forehead slopper, bigonion breadth, bignathion breadth, bignathion slopper.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.707-720
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• 2014

This paper proposes a face tracking scheme that is a combination of a face detection algorithm and a face tracking algorithm. The proposed face detection algorithm basically uses the Adaboost algorithm, but the amount of search area is dramatically reduced, by using skin color and motion information in the depth map. Also, we propose a face tracking algorithm that uses a template matching method with depth information only. It also includes an early termination scheme, by a spiral search for template matching, which reduces the operation time with small loss in accuracy. It also incorporates an additional simple refinement process to make the loss in accuracy smaller. When the face tracking scheme fails to track the face, it automatically goes back to the face detection scheme, to find a new face to track. The two schemes are experimented with some home-made test sequences, and some in public. The experimental results are compared to show that they outperform the existing methods in accuracy and speed. Also we show some trade-offs between the tracking accuracy and the execution time for broader application.

• Journal of radiological science and technology
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• v.44 no.6
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• pp.679-688
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• 2021

This study is a questionnaire about the lesson environment that radiation major students prefer in a non-face-to-face live online lesson environment for a total of 133 students, 65 second graders and 68 third graders who are enrolled in the department of radiology at a university located in the Seoul metropolitan area. And checked the satisfactory level by grade. The questionnaire consists of three categories: 1st real-time non-face-to-face lectures, 2nd professor lectures, and 3rd corona lectures. A total of 14 questions, with multiple choice and descriptive response methods. As an evaluation method, in the case of a multiple-choice question, the average was calculated using a 5-point Likert scale. As a result of conducting the independent sample T-test of the SPSS program, the response by grade was P > 0.05, and no significant result was shown by the contents of the questionnaire survey of the second grade. As for the lecture method of the department of radiology after the end of Covid-19 virus, it is better to promote face-to-face lessons in radiation training subjects and non-face-to-face real-time education in subjects centered on radiation theory.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.2
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• pp.11-20
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• 2010

In this paper we propose a face detection system which consists of a method of face candidate extraction using skin color and a method of face verification using the feature of facial structure. Firstly, the proposed extraction method of face candidate uses the image segmentation and merging algorithm in the regions of skin color and the neighboring regions of skin color. These two algorithms make it possible to select the face candidates from the variety of faces in the image with complicated backgrounds. Secondly, by using the partial face classifier, the proposed face validation method verifies the feature of face structure and then classifies face and non-face. This classifier uses face images only in the learning process and does not consider non-face images in order to use less number of training images. In the experimental, the proposed method of face candidate extraction can find more 9.55% faces on average as face candidates than other methods. Also in the experiment of face and non-face classification, the proposed face validation method obtains the face classification rate on the average 4.97% higher than other face/non-face classifiers when the non-face classification rate is about 99%.

• Journal of International Society for Simulation Surgery
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• v.3 no.2
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• pp.46-48
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• 2016

Purpose In face reocognition area, estimating occlusion in face images is on the rise. In this paper, we propose a new face recognition algorithm based on dual sparse representation to solve this problem. Method Each face image is partitioned into several pieces and sparse representation is implemented in each part. Then, some parts that have large sparse concentration index are combined and sparse representation is performed one more time. Each test sample is classified by using the final sparse coefficient where correlation between the test sample and training sample is applied. Results The recognition rate of the proposed algorithm is higher than that of the basic sparse representation classification. Conclusion The proposed method can be applied in real life which needs to identify someone exactly whether the person disguises his face or not.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.8
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• pp.1874-1884
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• 1996

In this paper, we proposed automatic searching algorithm of thresholding value using multilevel thresholding for face segmentation from input bust image effectively. The proposed algorithm extracted the thresholding value of brightness that is formed background region, face region and hair region without illumination, background and face size from input image. The statistical projection analysis project the brightness of multilevel thresholding image into horizontal and vertical direction and decide the thresholding value of face. And the algorithm extracted elliptical type block of face from input image in order to reduce the back ground region and hair region efficiently. The proposed algorithm can reduce searching area of feature extraction and processing time for face recognication.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.4
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• pp.43-54
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• 2007

This paper presents design and verification of a face detection hardware for real time application. Face detection algorithm detects rough face position based on already acquired feature parameter data. The hardware is composed of five main modules: Integral Image Calculator, Feature Coordinate Calculator, Feature Difference Calculator, Cascade Calculator, and Window Detection. It also includes on-chip Integral Image memory and Feature Parameter memory. The face detection hardware was verified by using S3C2440A CPU of Samsung Electronics, Virtex4LX100 FPGA of Xilinx, and a CCD Camera module. Our design uses 3,251 LUTs of Xilinx FPGA and takes about 1.96${\sim}$0.13 sec for face detection depending on sliding-window step size, when synthesized for Virtex4LX100 FPGA. When synthesized on Magnachip 0.25um ASIC library, it uses about 410,000 gates (Combinational area about 345,000 gates, Noncombinational area about 65,000 gates) and takes less than 0.5 sec for face realtime detection. This size and performance shows that it is adequate to use for embedded system applications. It has been fabricated as a real chip as a part of XF1201 chip and proven to work.

• Journal of The Geomorphological Association of Korea
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• v.19 no.3
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• pp.109-121
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• 2012

Rock-surface temperatures were observed at a trachytic lava dome, called as Baeknokdam Northwest Face, in the summit area of Mt. Halla, Jeju Island, to examine the frequency and occurrence season of freeze-thaw cycles and the rate of temperature changes during a freezing period. Long-term measurements were recorded over 18 months from November 2006 to April 2008, at a 1-hour logging interval and rock depth of 1.5 cm. Both diurnal freeze-thaw cycles and effective freeze-thaw cycles appear in larger numbers on a south-facing rock face than a north-facing rock face. The diurnal cycles were dominantly observed on February and March for the south face and on November and April for the north face, respectively. The annual freeze-thaw cycles were confirmed in terms of the presence of seasonal freezing periods lasting from mid-November to mid-April for the south face and from early-November to late-April for the north face, respectively. The rate of decreasing temperatures during the seasonal freezing periods is larger on the north face than the south face. Notwithstanding the lower numbers of freeze-thaw events, the north face experiences a higher frost intensity since the number of hours below $-3^{\circ}C$ is larger on the north face than the south face. The number of freeze-thaw events and the duration of days with continuous sub-zero rock temperatures largely depend on the solar radiation controlled by the aspect of the monitored rock surfaces, and thus the high-frequency short-term frost cycle dominantly appears on the south face and the annual frost cycle on the north face, respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.168-173
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• 2012

This paper presents a new human identification algorithm using partial features of the uncovered portion of face when a person wears a mask. After the face area is detected, the feature is extracted from the eye area above the mask. The identification process is performed by comparing the acquired one with the registered features. For extracting features SIFT(scale invariant feature transform) algorithm is used. The extracted features are independent of brightness and size- and rotation-invariant for the image. The experiment results show the effectiveness of the suggested algorithm.

• Steel and Composite Structures
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• v.29 no.3
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• pp.301-308
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• 2018

Properties of AFS vary with the changes in the face-sheet materials. Hence, the performance of AFS can be optimized by selecting face-sheet materials. In this work, three types of face-sheet materials representing elastic-perfectly plastic, elastic-plastic strain hardening and purely elastic materials were employed to study their effects on the flexural behavior and failure mechanism of AFS systematically. Result showed face-sheet materials affected the failure mechanism and energy absorption ability of AFS significantly. When the foam cores were sandwiched by aluminum alloy 6061, the AFS failed by face-sheet yielding and crack without collapse of the foam core, there was no clear plastic platform in the Load-Displacement curve. When the foam cores were sandwiched by stainless steel 304 and carbon fiber fabric, there were no face-sheet crack and the sandwich structure failed by core shear and collapse, plastic platform appeared. Energy absorption abilities of steel and carbon fiber reinforced AFS were much higher than aluminum alloy reinforced one. Carbon fiber was suggested as the best choice for AFS for its light weight and high performance. The versus strength ratio of face sheet to core was suggested to be a significant value for AFS structure design which may determine the failure mechanism of a certain AFS structure.