• Title/Summary/Keyword: Face color analysis

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An Integrated Face Detection and Recognition System (통합된 시스템에서의 얼굴검출과 인식기법)

  • 박동희;배철수
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.6
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    • pp.1312-1317
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    • 2003
  • This paper presents an integrated approach to unconstrained face recognition in arbitrary scenes. The front end of the system comprises of a scale and pose tolerant face detector. Scale normalization is achieved through novel combination of a skin color segmentation and log-polar mapping procedure. Principal component analysis is used with the multi-view approach proposed in[10] to handle the pose variations. For a given color input image, the detector encloses a face in a complex scene within a circular boundary and indicates the position of the nose. Next, for recognition, a radial grid mapping centered on the nose yields a feature vector within the circular boundary. As the width of the color segmented region provides an estimated size for the face, the extracted feature vector is scale normalized by the estimated size. The feature vector is input to a trained neural network classifier for face identification. The system was evaluated using a database of 20 person's faces with varying scale and pose obtained on different complex backgrounds. The performance of the face recognizer was also quite good except for sensitivity to small scale face images. The integrated system achieved average recognition rates of 87% to 92%.

Analysis of Sensibility Image According to Preference of Woman′s Golfwear (여성 골프웨어의 선호도에 따른 이미지 분석)

  • 구희경
    • Journal of the Korea Fashion and Costume Design Association
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    • v.3 no.2
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    • pp.87-106
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    • 2001
  • This study is to measure and evaluate the sensibility image for textile color and pattern design of woman's golfwear. Four-group colors and four patterns classified by a pracical survey on the market are presented. A questionnaire has 14 sensibility related words scaled by 7 point semantic differential method. The practical research is performed for 150 women screened by sensibility test for individual preference analysis based on the ages. Each subject is answered by a face-to-face interview method to improve survey's accuracy. For statistical results there are significant differences in treatment means of sensibility measurements according to the ages. Sensibility image for textile color and pattern design is significantly different according to individual character based on ages. In summary, this paper has proposed the sensibility image scale for textile color and pattern design of women's golfwears to satisfy individual sensibility according to ages. The results of this study can be effectively applied to develop textile color and pattern design based on human sensibility.

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An Intelligent Video Image Segmentation System using Watershed Algorithm (워터쉐드 알고리즘을 이용한 지능형 비디오 영상 분할 시스템)

  • Yang, Hwang-Kyu
    • The Journal of the Korea institute of electronic communication sciences
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    • v.5 no.3
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    • pp.309-314
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    • 2010
  • In this paper, an intelligent security camera over internet is proposed. Among ISC methods, watersheds based methods produce a good performance in segmentation accuracy. But traditional watershed transform has been suffered from over-segmentation due to small local minima included in gradient image that is input to the watershed transform. And a zone face candidates of detection using skin-color model. last step, face to check at face of candidate location using SVM method. It is extract of wavelet transform coefficient to the zone face candidated. Therefore, it is likely that it is applicable to read world problem, such as object tracking, surveillance, and human computer interface application etc.

Real Time Face Detection in Video Using Progressive Thresholding (순차 임계 설정법을 이용한 비디오에서의 실시간 얼굴검출)

  • Ye Soo-Young;Lee Seon-Bong;Kum Dae-Hyun;Kim Hyo-Sung;Nam Ki-Gon
    • Journal of the Institute of Convergence Signal Processing
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    • v.7 no.3
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    • pp.95-101
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    • 2006
  • A face detection plays an important role in face recognition, video surveillance, and human computer interaction. In this paper, we propose a progressive threshold method to detect human faces in real time. The consecutive face images are acquired from camera and transformed into YCbCr color space images. The skin color of the input images are separated using a skin color filter in the YCbCr color space and some candidated face areas are decided by connected component analysis. The intensity equalization is performed to avoid the effect of many circumstances and an arbitrary threshold value is applied to get binary images. The eye area can be detected because the area is clearly distinguished from others in the binary image progressive threshold method searches for an optimal eye area by progressively increasing threshold from low values. After progressive thresholding, the eye area is normalized and verified by back propagation algorithm to finalize the face detection.

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Realtime Face Recognition by Analysis of Feature Information (특징정보 분석을 통한 실시간 얼굴인식)

  • Chung, Jae-Mo;Bae, Hyun;Kim, Sung-Shin
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.12a
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    • pp.299-302
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    • 2001
  • The statistical analysis of the feature extraction and the neural networks are proposed to recognize a human face. In the preprocessing step, the normalized skin color map with Gaussian functions is employed to extract the region of face candidate. The feature information in the region of the face candidate is used to detect the face region. In the recognition step, as a tested, the 120 images of 10 persons are trained by the backpropagation algorithm. The images of each person are obtained from the various direction, pose, and facial expression. Input variables of the neural networks are the geometrical feature information and the feature information that comes from the eigenface spaces. The simulation results of$.$10 persons show that the proposed method yields high recognition rates.

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Realtime Face Recognition by Analysis of Feature Information (특징정보 분석을 통한 실시간 얼굴인식)

  • Chung, Jae-Mo;Bae, Hyun;Kim, Sung-Shin
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.9
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    • pp.822-826
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    • 2001
  • The statistical analysis of the feature extraction and the neural networks are proposed to recognize a human face. In the preprocessing step, the normalized skin color map with Gaussian functions is employed to extract the region of face candidate. The feature information in the region of the face candidate is used to detect the face region. In the recognition step, as a tested, the 120 images of 10 persons are trained by the backpropagation algorithm. The images of each person are obtained from the various direction, pose, and facial expression. Input variables of the neural networks are the geometrical feature information and the feature information that comes from the eigenface spaces. The simulation results of 10 persons show that the proposed method yields high recognition rates.

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Multi-views face detection in Omni-directional camera for non-intrusive iris recognition (비강압적 홍채 인식을 위한 전 방향 카메라에서의 다각도 얼굴 검출)

  • 이현수;배광혁;김재희;박강령
    • Proceedings of the IEEK Conference
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    • 2003.11b
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    • pp.115-118
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    • 2003
  • This paper describes a system of detecting multi-views faces and estimating their face poses in an omni-directional camera environment for non-intrusive iris recognition. The paper is divided into two parts; First, moving region is identified by using difference-image information. Then this region is analyzed with face-color information to find the face candidate region. Second part is applying PCA (Principal Component Analysis) to detect multi-view faces, to estimate face pose.

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Analysis of CIELuv Color feature for the Segmentation of the Lip Region (입술영역 분할을 위한 CIELuv 칼라 특징 분석)

  • Kim, Jeong Yeop
    • Journal of Korea Multimedia Society
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    • v.22 no.1
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    • pp.27-34
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    • 2019
  • In this paper, a new type of lip feature is proposed as distance metric in CIELUV color system. The performance of the proposed feature was tested on face image database, Helen dataset from University of Illinois. The test processes consists of three steps. The first step is feature extraction and second step is principal component analysis for the optimal projection of a feature vector. The final step is Otsu's threshold for a two-class problem. The performance of the proposed feature was better than conventional features. Performance metrics for the evaluation are OverLap and Segmentation Error. Best performance for the proposed feature was OverLap of 65% and 59 % of segmentation error. Conventional methods shows 80~95% for OverLap and 5~15% of segmentation error usually. In conventional cases, the face database is well calibrated and adjusted with the same background and illumination for the scene. The Helen dataset used in this paper is not calibrated or adjusted at all. These images are gathered from internet and therefore, there are no calibration and adjustment.

Comparison of recognition rate with distance on stereo face images base PCA (PCA기반의 스테레오 얼굴영상에서 거리에 따른 인식률 비교)

  • Park Chang-Han;Namkung Jae-Chan
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.1
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    • pp.9-16
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    • 2005
  • In this paper, we compare face recognition rate by distance change using Principal Component Analysis algorithm being input left and right image in stereo image. Change to YCbCr color space from RGB color space in proposed method and face region does detection. Also, after acquire distance using stereo image extracted face image's extension and reduce do extract robust face region, experimented recognition rate by using PCA algorithm. Could get face recognition rate of 98.61%(30cm), 98.91%(50cm), 99.05%(100cm), 99.90%(120cm), 97.31%(150cm) and 96.71%(200cm) by average recognition result of acquired face image. Therefore, method that is proposed through an experiment showed that can get high recognition rate if apply scale up or reduction according to distance.

The correlation of the skin color to the blood circulation on the face of Korean female between the ages of 30 and 45 (30${\sim}$40대 한국 여성의 안색과 혈행의 상관성 연구)

  • Kim, Eun-Joo;Roh, Ho-Sik;Kim, Su-Jong;Moon, Eun-Jeong;Kim, Duck-Hee;Kim, Han-Kon;Cho, Ga-Young
    • Journal of the Korean Institute of Oriental Medical Informatics
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    • v.14 no.2
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    • pp.73-79
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    • 2008
  • Objectives : We investigated the correlation of the skin color to blood circulation on the face of Korean female by noninvasive-skin measuring devices. Methods : Korean female(37.47${\pm}$3.66 years, n=36) aged 30-45 years were participated in this study. We measured the skin color of the face with Spectrophotometer CM2600d (Minolta, Japan) and the skin blood flow with Laser Doppler Imaging-Periscan PIM II (Perimed AB, Sweden). The skin color and blood circulation of three groups (30-35 years, 36-40 years, 41-45 years) divided on age were analyzed by paired-t test and regression analysis. Results : The L* values of the skin were decreased and the a* values were increased significantly with age. This means that the more age increase, the more the skin is dark and red. But the skin blood flow was not significantly different with age and skin color. Conclusions : In the oriental medicine, It was reported that the face of the female over 35 years is changed gradually haggard and the blood circulation is decreased. In our study, the blood circulation was not changed and the skin color was dark and red with increasing the age. We think this symptom resulted from the better nutrition than the past, the change of the blood-quality and this changes were too sensitive to be measured by Laser Doppler Imaging system.

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