The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
본 논문에서는 얼굴 감지를 위한 정규화된 RGB 색도 다이어그램을 기반으로 하는 새로운 색상 분할에 대해 설명합니다. 경계가 고정된 거친 피부 영역과 가변 경계가 있는 미세한 피부 영역을 사용하여 컬러 이미지에서 얼굴 피부를 추출합니다. 피부색과 비피부색의 피크가 두드러지는 두 가지 새로 개발된 히스토그램을 사용하여 피부 영역의 경계를 조정합니다. 제안된 접근 방식은 특정 카메라 매개 변수에 의존하고 일반적으로 특정 환경 조건으로 제한되는 피부색 모델이 필요하지 않으며 샘플 이미지가 필요하지 않습니다. 인터넷상의 87가지 서로 다른 리소스에서 얻은 다양한 조명 조건과 복잡한 배경에서 다양한 인종의 컬러 얼굴 이미지를 사용한 실험 결과는 11%의 높은 감지율을 나타냅니다. 탐지율과 계산 시간의 결과는 잘 알려진 Viola-Jones [12],[XNUMX]가 제안한 실시간 얼굴 탐지 방법과 유사합니다.
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Aryuanto SOETEDJO, Koichi YAMADA, "Skin Color Segmentation Using Coarse-to-Fine Region on Normalized RGB Chromaticity Diagram for Face Detection" in IEICE TRANSACTIONS on Information,
vol. E91-D, no. 10, pp. 2493-2502, October 2008, doi: 10.1093/ietisy/e91-d.10.2493.
Abstract: This paper describes a new color segmentation based on a normalized RGB chromaticity diagram for face detection. Face skin is extracted from color images using a coarse skin region with fixed boundaries followed by a fine skin region with variable boundaries. Two newly developed histograms that have prominent peaks of skin color and non-skin colors are employed to adjust the boundaries of the skin region. The proposed approach does not need a skin color model, which depends on a specific camera parameter and is usually limited to a particular environment condition, and no sample images are required. The experimental results using color face images of various races under varying lighting conditions and complex backgrounds, obtained from four different resources on the Internet, show a high detection rate of 87%. The results of the detection rate and computation time are comparable to the well known real-time face detection method proposed by Viola-Jones [11],[12].
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e91-d.10.2493/_p
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@ARTICLE{e91-d_10_2493,
author={Aryuanto SOETEDJO, Koichi YAMADA, },
journal={IEICE TRANSACTIONS on Information},
title={Skin Color Segmentation Using Coarse-to-Fine Region on Normalized RGB Chromaticity Diagram for Face Detection},
year={2008},
volume={E91-D},
number={10},
pages={2493-2502},
abstract={This paper describes a new color segmentation based on a normalized RGB chromaticity diagram for face detection. Face skin is extracted from color images using a coarse skin region with fixed boundaries followed by a fine skin region with variable boundaries. Two newly developed histograms that have prominent peaks of skin color and non-skin colors are employed to adjust the boundaries of the skin region. The proposed approach does not need a skin color model, which depends on a specific camera parameter and is usually limited to a particular environment condition, and no sample images are required. The experimental results using color face images of various races under varying lighting conditions and complex backgrounds, obtained from four different resources on the Internet, show a high detection rate of 87%. The results of the detection rate and computation time are comparable to the well known real-time face detection method proposed by Viola-Jones [11],[12].},
keywords={},
doi={10.1093/ietisy/e91-d.10.2493},
ISSN={1745-1361},
month={October},}
부
TY - JOUR
TI - Skin Color Segmentation Using Coarse-to-Fine Region on Normalized RGB Chromaticity Diagram for Face Detection
T2 - IEICE TRANSACTIONS on Information
SP - 2493
EP - 2502
AU - Aryuanto SOETEDJO
AU - Koichi YAMADA
PY - 2008
DO - 10.1093/ietisy/e91-d.10.2493
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E91-D
IS - 10
JA - IEICE TRANSACTIONS on Information
Y1 - October 2008
AB - This paper describes a new color segmentation based on a normalized RGB chromaticity diagram for face detection. Face skin is extracted from color images using a coarse skin region with fixed boundaries followed by a fine skin region with variable boundaries. Two newly developed histograms that have prominent peaks of skin color and non-skin colors are employed to adjust the boundaries of the skin region. The proposed approach does not need a skin color model, which depends on a specific camera parameter and is usually limited to a particular environment condition, and no sample images are required. The experimental results using color face images of various races under varying lighting conditions and complex backgrounds, obtained from four different resources on the Internet, show a high detection rate of 87%. The results of the detection rate and computation time are comparable to the well known real-time face detection method proposed by Viola-Jones [11],[12].
ER -