Human Face Detection via Characterized Convex Regional Relationship in Color Images

Chang-Woo PARK; Euntai KIM; Mignon PARK

Human Face Detection via Characterized Convex Regional Relationship in Color Images

Chang-Woo PARK, Euntai KIM, Mignon PARK

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In this letter, we propose a new method to detect faces in color images based on the characterized convex regional relationship. We detect skin and hair likeness regions using the derived skin and hair color models and the convex skin likeness and hair likeness regions are adopted as the characteristic convex regions. Finally, human faces can be detected via their intersection relationship. The proposed algorithm can accomplish face detection in an image including not only single face but also multi-faces and also detect deformed faces efficiently. To validity the effectiveness of the proposed method, we make experiments with various cases.

Publication: IEICE TRANSACTIONS on Information Vol.E86-D No.4 pp.759-762

Publication Date: 2003/04/01

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Type of Manuscript: LETTER

Category: Image Processing, Image Pattern Recognition

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Chang-Woo PARK, Euntai KIM, Mignon PARK, "Human Face Detection via Characterized Convex Regional Relationship in Color Images" in IEICE TRANSACTIONS on Information, vol. E86-D, no. 4, pp. 759-762, April 2003, doi: .
Abstract: In this letter, we propose a new method to detect faces in color images based on the characterized convex regional relationship. We detect skin and hair likeness regions using the derived skin and hair color models and the convex skin likeness and hair likeness regions are adopted as the characteristic convex regions. Finally, human faces can be detected via their intersection relationship. The proposed algorithm can accomplish face detection in an image including not only single face but also multi-faces and also detect deformed faces efficiently. To validity the effectiveness of the proposed method, we make experiments with various cases.
URL: https://globals.ieice.org/en_transactions/information/10.1587/e86-d_4_759/_p

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@ARTICLE{e86-d_4_759,
author={Chang-Woo PARK, Euntai KIM, Mignon PARK, },
journal={IEICE TRANSACTIONS on Information},
title={Human Face Detection via Characterized Convex Regional Relationship in Color Images},
year={2003},
volume={E86-D},
number={4},
pages={759-762},
abstract={In this letter, we propose a new method to detect faces in color images based on the characterized convex regional relationship. We detect skin and hair likeness regions using the derived skin and hair color models and the convex skin likeness and hair likeness regions are adopted as the characteristic convex regions. Finally, human faces can be detected via their intersection relationship. The proposed algorithm can accomplish face detection in an image including not only single face but also multi-faces and also detect deformed faces efficiently. To validity the effectiveness of the proposed method, we make experiments with various cases.},
keywords={},
doi={},
ISSN={},
month={April},}

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TY - JOUR
TI - Human Face Detection via Characterized Convex Regional Relationship in Color Images
T2 - IEICE TRANSACTIONS on Information
SP - 759
EP - 762
AU - Chang-Woo PARK
AU - Euntai KIM
AU - Mignon PARK
PY - 2003
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E86-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2003
AB - In this letter, we propose a new method to detect faces in color images based on the characterized convex regional relationship. We detect skin and hair likeness regions using the derived skin and hair color models and the convex skin likeness and hair likeness regions are adopted as the characteristic convex regions. Finally, human faces can be detected via their intersection relationship. The proposed algorithm can accomplish face detection in an image including not only single face but also multi-faces and also detect deformed faces efficiently. To validity the effectiveness of the proposed method, we make experiments with various cases.
ER -