• Title/Summary/Keyword: Skin Color Model

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Face Detection based on Multi-Channel Skin-Color Model (다채널 피부색 모델에 기반한 얼굴 영역 검출)

  • 김영권;고재필;변혜란
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.10b
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    • pp.433-435
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    • 2001
  • 얼굴 인식분야에서 실시간 얼굴검출에 대한 관심이 높아짐에 따라 피부색컬러 모델을 통한 얼굴영역검출에 대한 연구가 활발히 진행되고 있다. 그러나, 기존의 피부색 모델은 밝기 정보를 제거한 단일 채널의 색상모델이 대부분이다. 이에 본 논문에서는 얼굴피부색을 보다 효과적으로 모델링하기 위하여, 피부색 특성을 고려하여, 밝기 성분을 제거한 RGB 컬러를 모두 사용하는 H, Cb, Cg의 다채널 피부색 모델을 제시한다. 또한, 색상정보에서 사용하지 않은 밝기 정보는 영상 분할을 통해 사용한다. 제안하는 피부색 모델을 통한 얼굴영역 추출 과정을 보인다.

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Face Detection Using Active Contours (Active Contours를 사용한 얼굴 검출)

  • 정도준;장재식;박세현;김항준
    • Proceedings of the Korea Multimedia Society Conference
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    • 2002.05c
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    • pp.195-199
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    • 2002
  • 본 논문에서는 주어진 입력 이미지에서 얼굴 영역을 검출하기 위한 액티브 컨투어 모델(active contour models)을 제안한다. 제안한 모델은 스킨 칼라 모델(skin color model)에 의해 표현되는 사람 얼굴의 칼라 정보를 이용한다. 본 논문에서는 첨점(cusps), 모서리 (corners), 그리고 자동 위상 변화(automatic topological changes)를 고려한 레벨 셋 메소드(level set method)를 사용하여 액티브 컨투어를 진화시킨다. 실험 결과는 제안한 방법이 얼굴 영역 검출에 효과가 있음을 보여준다.

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Face Region Detection using a Color Union Model and The Levenberg-Marquadt Algorithm (색상 조합 모델과 LM(Levenberg-Marquadt)알고리즘을 이용한 얼굴 영역 검출)

  • Kim, Jin-Ok
    • The KIPS Transactions:PartB
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    • v.14B no.4
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    • pp.255-262
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    • 2007
  • This paper proposes an enhanced skin color-based detection method to find a region of human face in color images. The proposed detection method combines three color spaces, RGB, $YC_bC_r$, YIQ and builds color union histograms of luminance and chrominance components respectively. Combined color union histograms are then fed in to the back-propagation neural network for training and Levenberg-Marquadt algorithm is applied to the iteration process of training. Proposed method with Levenberg-Marquadt algorithm applied to training process of neural network contributes to solve a local minimum problem of back-propagation neural network, one of common methods of training for face detection, and lead to make lower a detection error rate. Further, proposed color-based detection method using combined color union histograms which give emphasis to chrominance components divided from luminance components inputs more confident values at the neural network and shows higher detection accuracy in comparison to the histogram of single color space. The experiments show that these approaches perform a good capability for face region detection, and these are robust to illumination conditions.

Identification of Apple Cultivars using Near-infrared Spectroscopy

  • Choi, Sun-Tay;Chung, Dae-Sung;Lim, Chai-Il;Chang, Kyu-Seob
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1624-1624
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    • 2001
  • Near-infrared spectroscopy (NIRS) was used to investigate the possibility for application in identification of apple cultivars. Three apple cultivars ‘Kamhong, Hwahong, and Fuji’ produced in Korea were scanned over the range of 1100-2500nm using NIRS (Infra Alzer 500). Two types of samples were used for scanning; one was apple with skin and the other was apple without skin. For cultivar identification, the NIR absorbance spectrums were analyzed by qualitative calibration in “Sesame” analysis program, and the various influence properties such as sugar contents, acidity, color, firmness, and micro-structure were compared in scanned samples. The ‘Kamhong’ cultivar could be identified from ‘Hwahong’ and ‘Fuji’ cultivars using the cluster model analysis. The test samples in calibration between ‘Kamhong’ and ‘Fuji’ cultivars could be completely identified. The test samples in calibration between ‘Kamhong’ and ‘Hwahong’ cultivars could be identified most of all. But, ‘Hwahong’ and ‘Fuji’ cultivars could not be quite classified each other. The apple skin influenced the identification process of apple cultivars. The samples without skin were more difficult to classify in calibration than the samples with skin. The physicochemical properties of apple cultivars showed like the result of identification in calibration using NIRS. Some physicochemical properties of ‘Kamhong’ cultivar were different from those of the other cultivars. Those of ‘Hwahong’ and ‘Fuji’ cultivars showed. similar to each other. The sucrose contents of ‘Kamhong’ cultivar were higher and the fructose contents and firmness of skin and flesh were lower than those of the others. The hypodermis layer of skin in ‘Kamhong’ cultivar was thinner than those of the others. In this studies, the identification of all apple cultivars by NIRS was not quite accurate because of the physicochemical properties which were different in the same cultivar, and inconsistent patterns by culivars in some properties. To solve these problems in NIRS application for apple cultivar identification, further study should be focused on the use of peculiar properties among the apple cultivars.

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HSV Color Model based Hand Contour Detector Robust to Noise (노이즈에 강인한 HSV 색상 모델 기반 손 윤곽 검출 시스템)

  • Chae, Soohwan;Jun, Kyungkoo
    • Journal of Korea Multimedia Society
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    • v.18 no.10
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    • pp.1149-1156
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    • 2015
  • This paper proposes the hand contour detector which is robust to noises. Existing methods reduce noises by applying morphology to extracted edges, detect finger tips by using the center of hands, or exploit the intersection of curves from hand area candidates based on J-value segmentation(JSEG). However, these approaches are so vulnerable to noises that are prone to detect non-hand parts. We propose the noise tolerant hand contour detection method in which non-skin area noises are removed by applying skin area detection, contour detection, and a threshold value. By using the implemented system, we observed that the system was successfully able to detect hand contours.

Rotation and Scale Invariant Face Detection Using Log-polar Mapping and Face Features (Log-polar변환과 얼굴특징추출을 이용한 크기 및 회전불변 얼굴인식)

  • Go Gi-Young;Kim Doo-Young
    • Journal of the Institute of Convergence Signal Processing
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    • v.6 no.1
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    • pp.15-22
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    • 2005
  • In this paper, we propose a face recognition system by using the CCD color image. We first get the face candidate image by using YCbCr color model and adaptive skin color information. And we use it initial curve of active contour model to extract face region. We use the Eye map and mouth map using color information for extracting facial feature from the face image. To obtain center point of Log-polar image, we use extracted facial feature from the face image. In order to obtain feature vectors, we use extracted coefficients from DCT and wavelet transform. To show the validity of the proposed method, we performed a face recognition using neural network with BP learning algorithm. Experimental results show that the proposed method is robuster with higher recogntion rate than the conventional method for the rotation and scale variant.

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Human Body Tracking and Pose Estimation Using CamShift Based on Kalman Filter and Weighted Search Windows (칼만 필터와 가중탐색영역 CAMShift를 이용한 휴먼 바디 트래킹 및 자세추정)

  • Min, Jae-Hong;Kim, In-Gyu;Hwang, Seung-Jun;Baek, Joong-Hwan
    • Journal of Advanced Navigation Technology
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    • v.16 no.3
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    • pp.545-552
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    • 2012
  • In this paper, we propose Modified Multi CAMShift Algorithm based on Kalman filter and Weighted Search Windows(KWMCAMShift) that extracts skin color area and tracks several human body parts for real-time human tracking system. We propose modified CAMShift algorithm that generates background model, extracts skin area of hands and head, and tracks the body parts. Kalman filter stabilizes tracking search window of skin area due to changing skin area in consecutive frames. Each occlusion areas is avoided by using weighted window of non-search areas and main-search area. And shadows are eliminated from background model and intensity of shadow. The proposed KWMCAMShift algorithm can estimate human pose in real-time and achieves 96.82% accuracy even in the case of occlusions.

Color stability of thermochromic pigment in maxillofacial silicone

  • Kantola, Rosita;Lassila, Lippo V.J.;Tolvanen, Mimmi;Valittu, Pekka K.
    • The Journal of Advanced Prosthodontics
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    • v.5 no.2
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    • pp.75-83
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    • 2013
  • PURPOSE. Maxillofacial silicone elastomer is usually colored intrinsically with color pigments to match skin colors. The purpose of this study was to investigate the color stability of a maxillofacial silicone elastomer, colored with a thermochromic, color changing pigment. MATERIALS AND METHODS. Disc-shaped maxillofacial silicone specimens were prepared and divided into 3 groups: a conventionally colored control group, one group additionally colored with 0.2 wt% thermochromic pigment, and one group with 0.6 wt% thermochromic pigment. Half of the surface of each specimen was covered with an aluminium foil. All of the specimens were exposed to UV radiation in 6 hour cycles over 46 days. In between the UV exposures, half of the specimens were stored in darkness, at room temperature, and the other half was stored in an incubator, at a humidity of 97% and a temperature of $+37^{\circ}C$. Color measurements were made with a spectrophotometer and registered according to the CIELAB $L^*a^*b^*$ color model system. The changes in $L^*$, $a^*$ and $b^*$ values during artificial aging were statistically analyzed by using paired samples t-test and repeated measures ANOVA. P-values <.05 were considered as statistically significant. RESULTS. The UV exposure resulted in visually noticeable and statistically significant color changes in the $L^*$, $a^*$ and $b^*$ values in both of the test groups containing thermochromic pigment. Storage in the incubator lead to statistically significant color changes in the $a^*$ and $b^*$ values of the specimens containing thermochromic pigment, compared to those stored at room temperature. CONCLUSION. The specimens containing thermochromic pigment were very sensitive to UV radiation, and the thermochromic pigment is not suitable, as such, to be used in maxillofacial prostheses.

Hybrid Color Model for Robust Detection of Skin Color under the Illumination Variance (조명 변화에 강건한 피부색 영역 검출을 위한 혼합 컬러 모델)

  • Moon, Kyu-Hyung;Choi, Yoo-Joo
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.10b
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    • pp.98-101
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    • 2006
  • 본 논문에서는 얼굴영상 인식의 전처리 단계인 피부 영역 자동 검출시 적용 가능하며 조명변화에 강건한 피부 영역 검출을 위한 혼합 컬러모델을 제시한다. 또한, 사용자별로 차이를 보이는 다양한 피부색을 자동으로 인식하고 사용자에 적합한 피부색 영역을 결정하기 위하여 제시한 컬러 모델을 기반으로 한 피부색 영역 모델링 전처리 단계를 제시한다. 우선, 사용자 및 사용 카메라에 따라 차이를 보이는 피부색에 대한 영역 모델을 구축하기 위하여 화면상의 가운데에 손이나 얼굴 영역이 위치하도록 하고 일정 프레임의 화면 정보를 취득한다. 취득 화면 정보로서 각 픽셀에 대한 정규화 된 RGB 성분 및 H 성분, V 성분 정보를 추출하고 이에 대한 평균화된 혼합 컬러 모델을 구축한다. H성분으로 피부색과 비슷한 배경을 제거하고 여기에 YUV 성분 중 적색에서 밝기 값을 뺀 성분인 V 값을 한 번 더 사용하여 밝기 값을 제거한 보다 뚜렷한 얼굴영역을 검출한다.

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A Study on Real-Time Detection System of Facial Region using Color Channel (컬러채널 실시간 복합 얼굴영역 검출 시스템 연구)

  • 송선희;석경휴;정유선;박동석;배철수;나상동
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2004.05b
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    • pp.463-467
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    • 2004
  • 본 논문에서는 컬러정보를 이용하여 외부 조명의 영향에 대응하면서 얼굴 후보영역을 추출하고, 추출된 후보 영역으로부터 다채널 스킨컬러 모델로 특정 정보를 추출하는 검출 기법을 제시한다. 외부 조명에 민감한 스킨컬러 특성을 고려해 색상정보와 광도를 분리할 수 있는 Y $C_{r}$ , $C_{b}$ 색상모델을 이용하며, Green, Blue 채널의 정보를 Gaussian 확률밀도 모델로부터 $C_{b-}$ $C_{g}$ 의 좁은 범위에 분포되어 있는 스킨컬러 영역 밀도를 모델링한다. 또한 얼굴영역에 Region Restricting과 임계값 반복 알고리즘을 사용하여 눈 영역 검출 과정을 보이고, 실시간 복합 얼굴 검출 시스템 조명방식에 의해 결과를 나타낸다.다.

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