• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.923-932
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• 2017

In this paper, we propose a GRNN(: Generalized Regression Neural Network) algorithms for new eyes and face recognition identification system to solve the points that need corrective action in accordance with the existing problems of facial movements gaze upon it difficult to identify the user and. Using a Kalman filter structural information elements of a face feature to determine the authenticity of the face was estimated future location using the location information of the current head and the treatment time is relatively fast horizontal and vertical elements of the face using a histogram analysis the detected. And the light obtained by configuring the infrared illuminator pupil effects in real-time detection of the pupil, the pupil tracking was to extract the text print vector. The abstract is to be in fully-justified italicized text as it is here, below the author information.

• 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.

• 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.

• Clinical and Experimental Pediatrics
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• v.52 no.6
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• pp.674-679
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• 2009

Purpose : The authors aimed to analyze the long-term effects of treatments, especially external beam radiotherapy (EBRT), in bilateral retinoblastoma patients. Methods : This retrospective study analyzed the medical records of 22 bilateral retinoblastoma patients who were registered between October, 1987 and October, 1998 and followed-up for more than 10 years. They were treated by enucleation, EBRT, and systemic chemotherapy. Age at diagnosis, sex, delay prior to treatment, Reese-Ellsworth (RE) classification, and the local treatment modalities were analyzed in relation to recurrence-free survival (RFS) and complications. Results : Median age at diagnosis was 7.0 months (range 1.7-31.6 months). Leukocoria was the most common presenting feature. Two patients had a familial history. The RE classifications of the 44 eyes were group II in 4, III in 14, IV in 4, and V in 22. At the end of a median follow-up period of 141 months (range 55-218 months), 20 patients were alive. The 10-year ocular survival rate of the 44 eyes was $56.8{\pm}7.5%$. The 10-year RFS and ocular survival rate of the 29 eyes treated by combined EBRT and chemotherapy were 75.9% and 86.2%, respectively. Treatment delay (>3 months) was found to be related to higher risk of recurrence. Complications after EBRT were cataract, retinal detachment, phthisis bulbi, and facial asymmetry. No patient developed a second malignancy during the follow-up period. Conclusion : Early detection and prompt treatment can increase ocular survival rates. In addition, careful attention should be paid to possible long-term sequelae in these patients.