• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.3
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• pp.72-78
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• 2000

In this study, we propose a model verification algorithm based on DCT and neural network for ATM security system. We construct database about facial images after capturing thirty persons facial images in the same lumination and distance. To simulate model verification, we capture four learning images and test images per a man. After detecting edge in facial images, we detect a characteristic area of square shape using edge distribution in facial images. Characteristic area contains eye bows, eyes, nose, mouth and cheek. We extract characteristic vectors to calculate diagonally coefficients sum after obtaining DCT coefficients about characteristic area. Characteristic vectors is normalized between +1 and -1, and then used for input vectors of neural networks. Not considering passwords, simulations results showed 100% verification rate when facial images were learned and 92% verification rate when facial images weren't learned. But considering passwords, the proposed algorithm showed 100% verification rate in case of two simulations.

• 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.

• Journal of the Korean Society of Radiology
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• v.10 no.8
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• pp.571-576
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• 2016

3D printing has recently been used in various fields. Among various applications, 3D face data must be generated for 3D face printing. A laser scanner is used to acquire 3D face data, but there is a restriction that a person should not move during scanning. In this paper, we propose a 3D face modeling method based on a single image and a face transformation system to use the generated 3D face for virtual cosmetic surgery. We have defined facial feature points from the 3D face database for 3D face data generation. After extracting feature points from a single face image, 3D face of the input face image is generated corresponding to the 3D face feature points defined from the 3D face database. After 3D face modeling, 3D face modification part is applied for use such as virtual cosmetic surgery.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.381-384
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• 2002

본 논문에서는 실험 영상으로부터 학습된 피부색상 정보를 이용하여 컬러 공간테이블을 생성한 후. 입력된 영상의 컬러와 공간정보를 학습된 피부색상 공간테이블로부터 비교, 분석하여 얼굴후보영역을 찾고자 하였다. 또한 추출된 후보영역의 레이블된 특징정보를 이용하여 지역적 특징을 찾아낸 후 얼굴 특징점의 위치에 따른 형태정보를 이용하여 신뢰할 수 있는 얼굴 영역을 검출하고자 하였다. 제안된 피부색상(Skin-tone)공간테이블은 변환하기 쉽고 계산이 빠른 RGB컬러 공간에서 실험, 평가되었으며, 실시간으로 입력된 영상의 정규화된 책상 값을 유사성 정도에 따라 레이블링하여 보다 빠른 얼굴 후보 영역의 검출과 검증을 할 수 있도록 하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.472-474
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• 2002

본 논문에서는 복잡한 영상에서 얼굴 영역의 윤곽선을 검출하는 방법을 제안하였다. 이를 위하여 얼굴의 칼라 정보에 기반한 액티브 컨투어 모델을 이용하였다. 얼굴의 칼라 정보는 색채칼라 공간(chromatic color space)에서 2D-Gaussian모델로 나타내어지는 스킨 칼로 모델로 표현 되었다. 실험결과 제안된 방법은 복잡한 영상뿐 아니라 잡음이 많은 영상에서 하나 또는 여러 개의 얼굴 영역을 추출할 수 있었다.

• Proceedings of the Korea Database Society Conference
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• 1995.12a
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• pp.183-186
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• 1995

본 논문에서는 연속적인 움직임을 가지는 얼굴 영상의 시퀀스에서 미리 정의한 몇개 특징점의 프레임 단위의 이동자취를 구하는 시스템을 구현하였다. 이를 위하여, 우선 얼굴영상에서의 특징점의 정의 및 그 추출과정을 보인다. 프레임간의 특징점들은 관성력으로 인하여 그 속도벡터가 급격히 변화할 수 없다는 평탄화 성질(smoothness)과, 이동후 다른 특징점들에 비해 근거리에 위치한다는 근접성 (proximity)을 가정하여 대응되는 쌍들을 구한다. 구현된 시스템을 실질적인 얼굴 영상의 시퀀스에 대해 실험하고, 그 결과를 보인다.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.223-225
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• 2004

얼굴 인식 및 검출에 있어서 어려운 문제가 조명의 변화와 포즈의 변화에 따른 성능 면에서의 신뢰성이다. 이러한 상황(Context)의 변화를 고려하여 영상을 처리하기 위하여 얼굴 영상에 주어진 조명의 상황을 SOM으로 분석하며, 영상에 따라 다른 전처리 기법의 필요성에 대해 제안한다. SOM은 비 지도학습으로써 얼굴 이미지들을 수집하여 그룹화 함으로써 상황분석을 위한 알고리즘으로 활용한다 이는 상황분석 기법을 적용하기 위한 응용에 활용할 수 있으며, 적절한 전처리 기법은 얼굴 인식의 성능을 향상시킴을 알 수 있었다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.4
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• pp.737-742
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• 2013

The surveillance system has been developed to be intelligent which can judge and cope by itself using human recognition technique. The existing face recognition is excellent at a short distance but recognition rate is reduced at a long distance. In this paper, we analyze the performance of face recognition according to interpolation and face recognition algorithm in face recognition using the multiple distance face images to training. we use the nearest neighbor, bilinear, bicubic, Lanczos3 interpolations to interpolate face image and PCA and LDA to face recognition. The experimental results show that LDA-based face recognition with bilinear interpolation provides performance in face recognition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.542-548
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• 2006

In this paper, we propose a face region detection/verification method using wavelet packet analysis and structural statistic for frontal human color image. The method extracts skin color lesions from input images, first. and then applies spatial restrictive conditions to the region, and determines whether the region is face candidate region or not. In second step, we find eye region in the face candidate region using structural statistic for standard korean faces. And in last step, the face region is verified via wavelet packet analysis if the face torture were satisfied to normal texture conditions.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.2
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• pp.1-9
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• 2018

In this paper, we propose a face recognition method which is not sensitive to illumination change and prevents false recognition of photographs. The proposed method uses infrared and depth images at the same time, solves sensitivity of illumination change by infrared image, and prevents false recognition of two - dimensional image such as photograph by depth image. Face detection method using infrared and depth images simultaneously and feature extraction and matching method for face recognition are realized. Simulation results show that accuracy of face recognition is increased compared to conventional methods.