• Archives of Craniofacial Surgery
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• v.13 no.2
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• pp.95-98
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• 2012

Nowadays, plastic surgical operations are increasingly being performed in Korea. We have gained added interest in this because some professional pictures contain plastic surgery in their venue. In the films, we intend to see the recognition of society for plastic surgeons and which field of plastic surgery. The list of movies for analysis were 'Plastic Beauty (1975)', 'Penthouse Elephant (2005)', '200 Pounds Beauty (2006)', 'Cinderella (2006)', and 'Time (2006)'. The TV dramas were 'She is looking (2005)', 'Lovers (2006-2007)', and 'Before & After Plastic Surgery Clinic (2008)'. Films were analyzed according to the following: the chief complaints and names of the operations, character of plastic surgeons, result of the operation and its possibility in reality, and its effect of plastic surgery on the life of the patients. Most of the film contained facial transplantation or the change of the face or body different from the original shape. Character type of the plastic surgeons was mostly medical realism, rather than ideal humanism. Most of the plastic surgeons have capability as a doctor; however, some of them had extramarital affairs. The surgery was successful in most of the cases, but were the patients happy with the results? This was not the case in the movies. In only one movie, '200 Pounds Beauty', the patient became happy; rest of them were eminently unhappy with the outcome. Why the discrepancy? It is difficult to analyze the minds of the people in the films, but considering that the majority of the characters in the films were rather unsavory, one may deduce that a crooked mind functions differently. Perhaps it is too much to hope for a day that will come when we will see a film that portrays the mental anguish that accompanies each and every procedure the Korean plastic surgeons make.

• Journal of the Korea Society of Computer and Information
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• v.16 no.6
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• pp.155-164
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• 2011

APP based on the smart phone is being utilized to various scopes such as medical services in hospitals, financing services at banks and credit card companies, and ubiquitous technologies in companies and homes etc. In this service environment, exposures of smart phones cause loss of assets including leaks of official/private information by outsiders. Though secret keys, pattern recognition technologies, and single image authentication techniques are being applied as protective methods, but they have problems in that accesses are possible by utilizing static key values or images like pictures. Therefore, this study proposes a face authentication technology for protecting smart phones from these dangerous factors and problems. The proposed technology authenticates users by extracting key frames of user's facial images by real time, and also controls accesses to the smart phone. Authentication information is composed of multiple key frames, and the user' access is controlled by distinction algorism of similarity utilizing DC values of image's pixel and luminance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.1A
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• pp.80-88
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• 2002

Visual media(image, graphic, and video) processing poses challenge from several perpectives, specifically from the point of view of real-time implementation and scalability. There have been several approaches to obtain speedups to meet the computing demands in multimedia processing ranging from media processors to special purpose implementations. A variety of parallel processing strategies are adopted in these implementations in order to achieve the required speedups. We have investigated a parallel processing system for improving the processing speed o f visual media related applications. The parallel processing system we proposed is similar to a pipelined memory stystem(MAMS). The multi-access memory system is made up of m memory modules and a memory controller to perform parallel memory access with a variety of combinations of 1${\times}$pq, pq${\times}$1, and p${\times}$q subarray, which improves both cost and complexity of control. Facial recognition, Phong shading, and automatic segmentation of moving object in image sequences are some that have been applied to the parallel processing system and resulted in faithful processing speed. This paper describes the parallel processing systems for the speedup and its utilization to three time-consuming applications.

• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.936-941
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• 2006

To apply object recognition techniques to real environment, illumination compensation method should be developed. As effective illumination compensation model, we focused our attention on Retinex model and illumination-Reflectance model, implemented them, and experimented on their performance. We implemented Retinex model with Single Scale Retinex, Multi-Scale Retinex, and Retinex Neural Network and Multi-Scale Retinex Neural Network, neural network model of Retinex model. Also, we implemented illumination-Reflectance model with reflectance image calculation by calculating an illumination image by low frequency filtering in frequency domain of Discrete Cosine Transform and Wavelet Transform, and Gaussian blurring. We compare their illumination compensation performance to facial images under nine illumination directions. We also compare their performance after post processing using Principal Component Analysis(PCA). As a result, illumination Reflectance model showed better performance and their overall performance was improved when illumination compensated images were post processed by PCA.

• The KIPS Transactions:PartB
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• v.18B no.1
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• pp.21-28
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• 2011

A 3D face shape derived from 2D images may be useful in many applications, such as face recognition, face synthesis and human computer interaction. To do this, we develop a fast 3D Active Appearance Model (3D-AAM) method using depth estimation. The training images include specific 3D face poses which are extremely different from one another. The landmark's depth information of landmarks is estimated from the training image sequence by using the approximated Jacobian matrix. It is added at the test phase to deal with the 3D pose variations of the input face. Our experimental results show that the proposed method can efficiently fit the face shape, including the variations of facial expressions and 3D pose variations, better than the typical AAM, and can estimate accurate 3D face shape from images.

• Journal of Genetic Medicine
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• v.17 no.1
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• pp.43-46
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• 2020

The Shprintzen-Goldberg syndrome (SGS) is an extremely rare genetic disorder caused by heterozygous variant in SKI. SGS is characterized by neurodevelopmental impairment with skeletal anomaly. Recognition of SGS is sometimes quite challenging in practice because it has diverse clinical features involving skeletal, neurological, and cardiovascular system. Here we report a case of a 6-month-old boy who initially presented with developmental delay and marfanoid facial features including prominent forehead, hypertelorism, high arched palate and retrognathia. He showed motor developmental delay since birth and could not control his head at the time of first evaluation. His height was above 2 standard deviation score. Arachnodactyly, hypermobility of joints, skin laxity, and pectus excavatum were also noted. Sequencing for FBN1 was negative, however, a novel missense variant, c.350G>A in SKI was identified by sequential whole exome sequencing. To our knowledge, this is the first case with SGS with phenotypic features of SGS overlapping with those of the Marfan syndrome, diagnosed by next generation sequencing in Korea.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.125-133
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• 2008

As society develops, the importance of safety for individuals and facilities in public places is getting higher. Not only the areas such as the existing parking lot, bank and factory which require security or crime prevention but also individual houses as well as general institutions have the trend to increase investment in guard and security. This study suggests face feature extract and the method to simply divide face region and head region that are import for face recognition by using color transform. First of all, it is to divide face region by using color transform of Y image of YIQ image and head image after dividing head region with K image among CMYK image about input image. Then, it is to extract features of face by using labeling after Log calculation to head image. The clearly divided head and face region can easily classify the shape of head and face and simply find features. When the algorism of the suggested method is utilized, it is expected that security related facilities that require importance can use it effectively to guard or recognize people.

• The Journal of Korean Institute of Information Technology
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• v.16 no.11
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• pp.105-113
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• 2018

In this paper, we proposed a method for effective classification of eye, nose, and mouth of human face. Most recent image classification uses Convolutional Neural Network(CNN). However, the features extracted by CNN are not sufficient and the classification effect is not too high. We proposed a new algorithm to improve the classification effect. The proposed method can be roughly divided into three parts. First, the Haar feature extraction algorithm is used to construct the eye, nose, and mouth dataset of face. The second, the model extracts CNN features of image using AlexNet. Finally, Haar-CNN features are extracted by performing convolution after Haar feature extraction. After that, CNN features and Haar-CNN features are fused and classify images using softmax. Recognition rate using mixed features could be increased about 4% than CNN feature. Experiments have demonstrated the performance of the proposed algorithm.

• Archives of Craniofacial Surgery
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• v.22 no.4
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• pp.193-198
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• 2021

Background: Nasal bone fractures are frequently encountered in clinical practice. Although fracture reduction is simple and correction requires a short operative time, low patient satisfaction and relatively high complication rates remain issues for many surgeons. These challenges may result from inaccuracies in fracture recognition and assessment or inappropriate surgical planning. Findings from immediate postoperative computed tomography (CT) scans and those performed at 4 to 6 weeks postoperatively were compared to evaluate the accuracy and outcomes of nasal fracture reduction. Methods: This retrospective study included patients diagnosed with nasal bone fractures at our department who underwent closed reduction surgery. Patients who did not undergo additional CT scans were excluded from the study. Clinical examinations, patient records, and radiographic images were evaluated in 20 patients with nasal bone fractures. Results: CT findings from immediately after surgery and a 1month follow-up were compared in 20 patients. Satisfactory nasal projection and aesthetically acceptable results were observed in patients with accurate correction or mild overcorrection, while undercorrection was associated with unfavorable results. Conclusion: Closed reduction surgery for correcting nasal bone fractures usually provides acceptable outcomes with relatively few complications. If available, immediate postoperative CT scans are recommended to guide surgeons in the choice of whether to perform secondary adjustments if the initial results are unsatisfactory. Based on photogrammetric data, nasal bone reduction with accurate correction or mild overcorrection achieved acceptable and stable outcomes at 1 month postoperatively. Therefore, when upward dislocation is observed on postoperative CT, one can simply observe without a subsequent intervention.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.89-96
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• 2021

The number of confirmed cases of coronavirus-19 is soaring around the world and has caused numerous deaths. Wearing a mask is very important to prevent infection. Incidents and accidents have occurred due to the recommendation to wear a mask in public places such as buses and subways, and it has emerged as a serious social problem. To solve this problem, this paper proposes an open source-based face mask wearing monitoring system. We used open source software, web-based artificial intelligence tool teachable machine and open source hardware Arduino. It judges whether the mask is worn, and performs commands such as guidance messages and alarms. The learning parameters of the teachable machine were learned with the optimal values of 50 learning times, 32 batch sizes, and 0.001 learning rate, resulting in an accuracy of 1 and a learning error of 0.003. We designed and implemented a mask wearing monitoring system that can perform commands such as guidance messages and alarms by determining whether to wear a mask using a web-based artificial intelligence tool teachable machine and Arduino to prove its validity.