• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.681-687
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• 2007

Face recognition technique is very popular for a personal information security and user identification in recent years. However, the face recognition system is very hard to be implemented due to the difficulty where change in illumination, pose and facial expression. In this paper, we consider that an illumination change causing the variety of face appearance, virtual image data is generated and added to the D-LDA which was selected as the most suitable feature extractor. A less sensitive recognition system in illumination is represented in this paper. This way that consider nature of several illumination directions generate the virtual training image data that considered an illumination effect of the directions and the change of illumination density. As result of experiences, D-LDA has a less sensitive property in an illumination through ORL, Yale University and Pohang University face database.

• Archives of Plastic Surgery
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• v.34 no.1
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• pp.44-51
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• 2007

Purpose: Blow-out fracture is one of the most common fractures in facial trauma. It is diagnosed by Computed Tomography(CT) scan, which is considered as the most effective diagnostic tool. Since, the Picture Archiving Communication System(PACS) has been provided recently to many hospitals, doctors are more familiar with imaging software of PACS. Because this software has many useful measuring tools, doctors can measure orbital structure easily and make a plan for treatment with its data. Therefore, authors intended to analyze the data of orbital structure measured with PACS imaging software and evaluate its usefulness. Methods: The charts and CT images of 100 patients, which were 50 patients with medial wall fracture and 50 patients with floor fracture, were reviewed. Patients were selected by pre-determined criteria and their CT images were measured with image software of PACS. 'Extraocular muscle thickness', 'Defect ratio'(ratio of defect area to normal area) and 'Globe position index' were measured and analyzed statistically. Results: The thickness of inferior rectus muscle and medial rectus muscle was simultaneously increased in acute-stage of blow-out fracture. The medial rectus muscle was more thickened in medial wall fracture and inferior rectus was more thickened in floor fracture, respectively. In acute blow-out fracture, globe position is exophthalmic rather than enophthalmic. Especially in floor fracture, numerical value summed up thickness of all extraocular muscle is correlated to the defect ratio and globe position index. Conclusion: Clinicians can decide globe position or presume defect ratio in inferior wall fracture by measurement of CT image in acute blow-out fracture using PACS.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.3
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• pp.205-208
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• 2013

Generally, binary pattern transforms have been used in the field of the face recognition and facial expression, since they are robust to illumination. Thus, this paper proposes an illumination-robust face recognition system combining an MLDP, which improves the texture component of the LDP, and a 2D-PCA algorithm. Unlike that binary pattern transforms such as LBP and LDP were used to extract histogram features, the proposed method directly uses the MLDP image for feature extraction by 2D-PCA. The performance evaluation of proposed method was carried out using various algorithms such as PCA, 2D-PCA and Gabor wavelets-based LBP on Yale B and CMU-PIE databases which were constructed under varying lighting condition. From the experimental results, we confirmed that the proposed method showed the best recognition accuracy.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.748-753
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• 2012

In this paper, Face recognition algorithm is designed based on optimized pRBFNNs pattern classifier using three-dimensional scanner. Generally two-dimensional image-based face recognition system enables us to extract the facial features using gray-level of images. The environmental variation parameters such as natural sunlight, artificial light and face pose lead to the deterioration of the performance of the system. In this paper, the proposed face recognition algorithm is designed by using three-dimensional scanner to overcome the drawback of two-dimensional face recognition system. First face shape is scanned using three-dimensional scanner and then the pose of scanned face is converted to front image through pose compensation process. Secondly, data with face depth is extracted using point signature method. Finally, the recognition performance is confirmed by using the optimized pRBFNNs for solving high-dimensional pattern recognition problems.

• Archives of Craniofacial Surgery
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• v.22 no.2
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• pp.85-92
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• 2021

Background: Patients with secondary deformities associated with unilateral cleft lip and nose might also suffer from nostril stenosis due to a lack of tissue volume in the nostril on the cleft side. Here, we used full-thickness skin grafts (FTSGs) to reduce nostril stenosis and various methods for skin volume augmentation. We compared the changes in the symmetry of both nostrils before and after surgery. Methods: From February 2016 to January 2020, 34 patients underwent secondary cheiloplasty and open rhinoplasty for secondary deformities of the unilateral cleft lip and nose with nostril stenosis. FTSG was used on the nostril floor, nasal columella, and alar inner lining. The measured nasal profile included the nostril surface, nostril circumference, width of the nostril floor, and distance from the alar-facial groove to the nasal tip. The "overlap area," which was defined as the largest overlapping area when the image of the cleft nostril was flipped to the left and right and overlaid on the image of the normal side nostril, was also calculated. The degree of symmetry was evaluated by dividing the value of the cleft side by that of the normal side of each measured profile and expressed as "ratios." Results: The results of all profile ratios, except for the nostril floor width, became significantly close to 1, which represents full symmetry. The overlap area ratio improved from 62.7% to 77.3%, meaning that the length and width of the nostril as well as the overall shape became similar (p< 0.05). Conclusion: When performing cleft rhinoplasty with nostril stenosis, FTSG is useful to achieve symmetry in the nostril size and shape. Skin grafting is simpler to perform than the other types of local flap, and the results are generally satisfactory.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.115-121
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• 2020

With the spread of IoT technology, various IoT applications using facial recognition are emerging. This paper describes the design and implementation of a remote control system using deep learning-based face recognition and hand gesture recognition. In general, an application system using face recognition consists of a part that takes an image in real time from a camera, a part that recognizes a face from the image, and a part that utilizes the recognized result. Raspberry PI, a single board computer that can be mounted anywhere, has been used to shoot images in real time, and face recognition software has been developed using tensorflow's FaceNet model for server computers and hand gesture recognition software using OpenCV. We classified users into three groups: Known users, Danger users, and Unknown users, and designed and implemented an application that opens automatic door locks only for Known users who have passed both face recognition and hand gestures.

• Korean Journal of Community Nutrition
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• v.28 no.2
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• pp.114-123
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• 2023

Objectives: Current social norms in the United States do not favor breastfeeding in public. This study examined associations between college students' explicit and implicit emotions of breastfeeding in public and their intention to support public breastfeeding. Methods: Twenty-two student participants viewed images of a breastfeeding woman with a fully-covered, fully-exposed, or partially-exposed breast in a public setting. After viewing each image, participants' explicit emotions (self-reported) of the image were measured using a questionnaire and their implicit emotions (facial expression) were measured using FaceReader technology. We examined if a relationship exists between both emotions [toward images] and intention to support breastfeeding in public using correlation techniques. We determined the relative influence of two emotions on the intention to support breastfeeding in public using regression analyses. Results: The nursing images depicting a fully-covered breast (r = 0.425, P = 0.049 vs. r = 0.271, P = 0.222) and fully-exposed breast (r = 0.437, P = 0.042 vs. r = 0.317, P = 0.150) had stronger associations with explicit emotions and intention to support breastfeeding in public compared to implicit emotions and intention. Breastfeeding knowledge was associated with a positive explicit emotion for images with partial- (β = 0.60, P = 0.003) and full-breast exposure (β = 0.65, P = 0.002). Conclusions: Explicit emotions appear to drive stated intentions to support public breastfeeding. Further research is needed to understand the disconnect between explicit and implicit emotions, the factors that influence these emotions, and whether stated intentions lead to consistent behavior.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.179-186
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• 2023

For the future prosperity of any society, the sound growth of children is essential. Autism Spectrum Disorder (ASD) is a neurobehavioral disorder which has an impact on social interaction of autistic child and has an undesirable effect on his learning, speaking, and responding skills. These children have over or under sensitivity issues of touching, smelling, and hearing. Its symptoms usually appear in the child of 4- to 11-year-old but parents did not pay attention to it and could not detect it at early stages. The process to diagnose in recent time is clinical sessions that are very time consuming and expensive. To complement the conventional method, machine learning techniques are being used. In this way, it improves the required time and precision for diagnosis. We have applied TFLite model on image based dataset to predict the autism based on facial features of child. Afterwards, various machine learning techniques were trained that includes Logistic Regression, KNN, Gaussian Naïve Bayes, Random Forest and Multi-Layer Perceptron using Autism Spectrum Quotient (AQ) dataset to improve the accuracy of the ASD detection. On image based dataset, TFLite model shows 80% accuracy and based on AQ dataset, we have achieved 100% accuracy from Logistic Regression and MLP models.

• Fashion & Textile Research Journal
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• v.16 no.6
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• pp.995-1000
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• 2014

This study, using the free language association method, examined the characteristics of emotional words of respondents who were exposed to facial photos of women in 60s, and favorableness and favorable styles of them. To analyze mood characteristics on the faces, they were divided into positive mood words and negative mood words. Following previous researches, they were divided into introversion, extraversion, and ambiversion. It was found that the proportion of positive emotional words respondents used was 37%, and that of negative ones was 63%, demonstrating that respondents are more likely than not to get the negative impressions from the faces of their contemporaries. The characteristics of the words consists of 38% introversion, 47% extraversion, and 14% ambiversion. And, respondents used the words like 'beautiful' and 'good-looking' to the stimuli to which they felt favorable, and 'ill-tempered' and 'stubborn' to the stimuli to which they felt unfavorable. Third, the most favorable style to both male and female respondents in 60s were sentimental and good-mannered. They generally favor women who are soft and caring, and dislike talkative, snobbish, and thick make-up women. The analysis results in this paper may help image making and personal relations. Further study needs to expand the survey area to ensure more significant influence on the social life and interpersonal relationship of senior citizens.

• Journal of Korea Multimedia Society
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• v.15 no.1
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• pp.63-70
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• 2012

In this paper an extension to an original active shape model(ASM) for facial feature extraction is presented. The original ASM suffers from poor shape alignment by aligning the shape model to a new instant of the object in a given image using a simple similarity transformation. It exploits only informations such as scale, rotation and shift in horizontal and vertical directions, which does not cope effectively with the complex pose variation. To solve the problem, new shape alignment with 6 degrees of freedom is derived, which corresponds to an affine transformation. Another extension is to speed up the calculation of the Mahalanobis distance for 2-D profiles by trimming the profile covariance matrices. Extensive experiment is conducted with several images of varying poses to check the performance of the proposed method to segment the human faces.