• 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 Korea Society of Computer and Information
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• v.18 no.11
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• pp.167-174
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• 2013

TIn this paper, we find the face in color images and the ability to track the face was implemented. Face tracking is the work to find face regions in the image using the functions of the computer system and this function is a necessary for the robot. But such as extracting skin color in the image face tracking can not be performed. Because face in image varies according to the condition such as light conditions, facial expressions condition. In this paper, we use the skin color pixel extraction function added lighting compensation function and the entire processing system was implemented, include performing finding the features of eyes, nose, mouth are confirmed as face. Lighting compensation function is a adjusted sine function and although the result is not suitable for human vision, the function showed about 4% improvement. Face features are detected by amplifying, reducing the value and make a comparison between the represented image. The eye and nose position, lips are detected. Face tracking efficiency was good.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.288-296
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• 2021

Automated face recognition in a runtime environment is gaining more and more important in the fields of surveillance and urban security. This is a difficult task keeping in mind the constantly volatile image landscape with varying features and attributes. For a system to be beneficial in industrial settings, it is pertinent that its efficiency isn't compromised when running on roads, intersections, and busy streets. However, recognition in such uncontrolled circumstances is a major problem in real-life applications. In this paper, the main problem of face recognition in which full face is not visible (Occlusion). This is a common occurrence as any person can change his features by wearing a scarf, sunglass or by merely growing a mustache or beard. Such types of discrepancies in facial appearance are frequently stumbled upon in an uncontrolled circumstance and possibly will be a reason to the security systems which are based upon face recognition. These types of variations are very common in a real-life environment. It has been analyzed that it has been studied less in literature but now researchers have a major focus on this type of variation. Existing state-of-the-art techniques suffer from several limitations. Most significant amongst them are low level of usability and poor response time in case of any calamity. In this paper, an improved face recognition system is developed to solve the problem of occlusion known as FRS-OCC. To build the FRS-OCC system, the color and texture features are used and then an incremental learning algorithm (Learn++) to select more informative features. Afterward, the trained stack-based autoencoder (SAE) deep learning algorithm is used to recognize a human face. Overall, the FRS-OCC system is used to introduce such algorithms which enhance the response time to guarantee a benchmark quality of service in any situation. To test and evaluate the performance of the proposed FRS-OCC system, the AR face dataset is utilized. On average, the FRS-OCC system is outperformed and achieved SE of 98.82%, SP of 98.49%, AC of 98.76% and AUC of 0.9995 compared to other state-of-the-art methods. The obtained results indicate that the FRS-OCC system can be used in any surveillance application.

• The Research Journal of the Costume Culture
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• v.32 no.3
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• pp.398-418
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• 2024

This study aims to examine how the body and clothing of Jesus Christ are represented in the Russian Transfiguration of Christ icons of the 15th and 16th centuries and why it is considered to have established a distinct Russian iconography free from Byzantine influence. The study analyzes the Russian icons comparing them with their Byzantine prototypes to identify the distinctive 'Russianness' of the representation. The research methods comprise a qualitative analysis of the literature on Russian Orthodoxy, Russian icons, Christian theology, and Christ's clothing and an empirical analysis of the icons. The scope of the study is limited to Russian icons from the 15th and 16th centuries and Byzantine icons from the 9th century onwards. The study found that, compared to Byzantine icons, the Russian icons exhibit a more elongated body, darker facial features, and lighter clothing. A statistical analysis using the Mann-Whitney U test further revealed that the Russian icons feature a stiffer, simpler form, more opaque material, and more defined clothing boundaries. These stylistic differences suggest that the 'Russianness' in the expression of Christ's body and clothing in the Transfiguration of Christ icons derives from creativity, abstractness, and tradition. Rather than a simple recreation of the historical Christ or adherence to the Byzantine tradition, the Russian iconographic representation emphasizes Christ's transfiguration into a luminous form, as described in the Bible, accentuating his divine nature over his human aspects.

• Anatomy and Cell Biology
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• v.57 no.1
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• pp.25-30
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• 2024

The aim of this study was to identify the anatomical feature of retaining ligament and fat compartment on the lower eyelid and infraorbital region using a histological method, and to investigate clear definitions for them which could be used generally in the clinical area. Eighteen specimens from eight fresh Korean cadavers were stained with Masson trichrome or hematoxylin and eosin. The ligamentous and fascial fibrous tissue were clearly identified. The ligamentous fibrous tissue which traversed in the superficial and deep fat layer was skin ligament and orbicularis retaining ligament (ORL). The fascial fibrous tissue enclosed the orbicularis oculi muscle (OOc) and circumferencial adipose tissue. Based on the ligamentous and fascial structure, three fat compartments, septal, suborbicularis oculi and infraorbital fat compartment, could be identified. The OOc attached to orbital rim and dermis by ORL and skin ligament, and the muscle fascicle and fat fascicle provided the connection point to the ORL and skin ligament as enclosing all muscle and fat tissue. The combination of the force made by the skin ligament in the lower eyelid and ORL may decide the level and form of the infraorbital grooves.

• The korean journal of orthodontics
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• v.26 no.2 s.55
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• pp.205-218
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• 1996

A given facial type can be considered as a syndrome in which various features are aggregated, so a single parameter is not sufficient to accurately identify a given facial type. This study was designed to identify & characterize the skeletal types that blend under the headline-'Cl III,deepbite'. Cephalograms of thirty-four untreated mixed dentition patients, selected mainly on the basis of clinical impression of Cl III with reduced lower face heights were studied. The following conclusion can be drawn. 1. Cl III malocclusion with reduced lower face height could be classified into three types. 2. Subtype 1 was identified by the following features : strong ramus, more anteriorly positioned upper molars without alveolar hypoplasia, acutely reduced Mn. plane angle. 3. Subtype 2 was characterized by a short ramus, sharply reduced postrior alveolar height, and normal Mn. plane angle. In general, this type had hypoplasia tendency in the vertical dimension. 4. In subtype 3, the AUFH occupying more percentage than ALFH was a outstanding feature. Ramal height was in normal range, alveolar hypoplasia and slightly reduced Mn. plane angle was observed. 5. The features of the subtypes were reflected in certain indices, which can be regarded as discriminative index. LAFH: if reduced, regardless of subtypes, indicates reduced lower ant. face height consistently. FHR: when this ratio is increased, it indicates subtype 1. FHI: when this ratio is in normal range, it indicates subtype 2. FPI: if reduced greatly, it indicates subtype 3.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.3 s.309
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• pp.30-38
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• 2006

In this paper, we improved to drops recognition rate according to distance using distance and depth information with 3D from stereo face images. A monocular face image has problem to drops recognition rate by uncertainty information such as distance of an object, size, moving, rotation, and depth. Also, if image information was not acquired such as rotation, illumination, and pose change for recognition, it has a very many fault. So, we wish to solve such problem. Proposed method consists of an eyes detection algorithm, analysis a pose of face, md principal component analysis (PCA). We also convert the YCbCr space from the RGB for detect with fast face in a limited region. We create multi-layered relative intensity map in face candidate region and decide whether it is face from facial geometry. It can acquire the depth information of distance, eyes, and mouth in stereo face images. Proposed method detects face according to scale, moving, and rotation by using distance and depth. We train by using PCA the detected left face and estimated direction difference. Simulation results with face recognition rate of 95.83% (100cm) in the front and 98.3% with the pose change were obtained successfully. Therefore, proposed method can be used to obtain high recognition rate with an appropriate scaling and pose change according to the distance.

• Childhood Kidney Diseases
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• v.5 no.2
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• pp.188-195
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• 2001

Type II membranoproliferative glomerulonephritis (Dense deposit disease) is an acquired primary glomerular disease characterized by electron microscopic evidence of a continuous dense membrane deposition replacing the lamina densa. It is a subtype of idiopathic membra- noproliferative glomerulonephritis, and was described as a separate entity by Berger and Galle in 1963. It frequently occurs in older chilren and young adults and the clinical course is variable, but is generally progressive. The presenting feature is nephrotic syndrome in many patients, and proteinuria and hematuria are also seen frequently. The purpose of this paper is to present a case of DDD (Dense deposit disease) from a 10 year old boy who was diagnosed as a acute poststreptococcal glomurulonephritis with protenuria, hematuria, and facial edema by renal biopsy 4 years ago. (J, Korean Soc Pediatr Nephrol 2001 ; 5 : 188-95)

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1501-1514
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• 2008

The face shape extracted by the depth values has different appearance as the most important facial information. The face images decomposed into frequency subband are signified personal features in detail. In this paper, we develop a method for recognizing the range face images by multiple frequency domains for each depth image using the modified fuzzy c-mean algorithm. For the proposed approach, the first step tries to find the nose tip that has a protrusion shape on the face from the extracted face area. And the second step takes into consideration of the orientated frontal posture to normalize. Multiple contour line areas which have a different shape for each person are extracted by the depth threshold values from the reference point, nose tip. And then, the frequency component extracted from the wavelet subband can be adopted as feature information for the authentication problems. The third step of approach concerns the application of eigenface to reduce the dimension. And the linear discriminant analysis (LDA) method to improve the classification ability between the similar features is adapted. In the last step, the individual classifiers using the modified fuzzy c-mean method based on the K-NN to initialize the membership degree is explained for extracted coefficient at each resolution level. In the experimental results, using the depth threshold value 60 (DT60) showed the highest recognition rate among the extracted regions, and the proposed classification method achieved 98.3% recognition rate, incase of fuzzy cluster.

• Journal of the korean academy of Pediatric Dentistry
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• v.43 no.3
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• pp.313-319
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• 2016

Wolf-Hirschhorn syndrome (WHS), associated with the deletion of the short arm of chromosome 4, causes multiple congenital malformations. Patients suffer from various deformities, including mental and growth disorders, epilepsy, hypotonia, congenital heart defects, and atypical craniofacial features. The "Greek warrior helmet appearance" is the most characteristic feature, with a prominent glabella, high arched eyebrow, broad nasal bridge, and hypertelorism. Cleft lip with or without cleft palate is observed in 30% of patients. Dental structure anomalies also exist including multiple tooth agenesis and over-retained primary molars caused by MSX1 gene impairment, and cone-shaped and taurodontic teeth. This case, a 9-year-old girl with WHS, showed intellectual disability, delayed growth development, previous occurrence of seizures, otitis media, and the typical facial features of WHS. Dental findings included multiple congenital missing teeth, over-retained primary teeth, and severe caries on the primary molars. Dental treatments were performed under general anesthesia. This report documents the characteristics of WHS, including general and oral features, and discusses the importance of oral hygiene and preventive dental management.