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- Publisher Website: 10.1109/CYBER50695.2020.9279170
- Scopus: eid_2-s2.0-85099071774
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Conference Paper: Human Face Feature Extraction Based on a Partition Threshold Model
Title | Human Face Feature Extraction Based on a Partition Threshold Model |
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Authors | |
Keywords | face extraction binarization partition threshold complex lighting |
Issue Date | 2020 |
Publisher | IEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1800486 |
Citation | 2020 10th Institute of Electrical and Electronics Engineers International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), Xi'an, China, 10-13 October 2020, p. 271-276 How to Cite? |
Abstract | Image feature extraction technology has been applied to all aspects of our lives, such as science, education, aerospace, national defence, and industrial production. For example, a painting robot requires a face extraction method that meets human aesthetic standards. This paper mainly aims to solve the problem of conditional binary extraction of the human face against changeable and complex backgrounds, and under different lighting environments, in order to achieve better human face image feature extraction and higher image processing speeds - the average time to process one image is 3.3 seconds. Different from the traditional partition method, which only uses the pixel value information, our method combines a skin colour model, the edge structure of the face, and pixel information in the partition. The partition threshold model proposed in this paper is used to calculate the appropriate threshold value in each partition, so that each image partition gets the corresponding threshold value. Experimental results demonstrate the robustness of the scheme. |
Persistent Identifier | http://hdl.handle.net/10722/309344 |
ISSN |
DC Field | Value | Language |
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dc.contributor.author | Tian, Y | - |
dc.contributor.author | Wang, S | - |
dc.contributor.author | Bi, S | - |
dc.contributor.author | Xi, N | - |
dc.date.accessioned | 2021-12-29T02:13:46Z | - |
dc.date.available | 2021-12-29T02:13:46Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | 2020 10th Institute of Electrical and Electronics Engineers International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), Xi'an, China, 10-13 October 2020, p. 271-276 | - |
dc.identifier.issn | 2379-7711 | - |
dc.identifier.uri | http://hdl.handle.net/10722/309344 | - |
dc.description.abstract | Image feature extraction technology has been applied to all aspects of our lives, such as science, education, aerospace, national defence, and industrial production. For example, a painting robot requires a face extraction method that meets human aesthetic standards. This paper mainly aims to solve the problem of conditional binary extraction of the human face against changeable and complex backgrounds, and under different lighting environments, in order to achieve better human face image feature extraction and higher image processing speeds - the average time to process one image is 3.3 seconds. Different from the traditional partition method, which only uses the pixel value information, our method combines a skin colour model, the edge structure of the face, and pixel information in the partition. The partition threshold model proposed in this paper is used to calculate the appropriate threshold value in each partition, so that each image partition gets the corresponding threshold value. Experimental results demonstrate the robustness of the scheme. | - |
dc.language | eng | - |
dc.publisher | IEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1800486 | - |
dc.relation.ispartof | IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER) | - |
dc.rights | IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER). Copyright © IEEE. | - |
dc.rights | ©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | - |
dc.subject | face extraction | - |
dc.subject | binarization | - |
dc.subject | partition threshold | - |
dc.subject | complex lighting | - |
dc.title | Human Face Feature Extraction Based on a Partition Threshold Model | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Bi, S: shengbi@hku.hk | - |
dc.identifier.email | Xi, N: xining@hku.hk | - |
dc.identifier.authority | Xi, N=rp02044 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/CYBER50695.2020.9279170 | - |
dc.identifier.scopus | eid_2-s2.0-85099071774 | - |
dc.identifier.hkuros | 331212 | - |
dc.identifier.spage | 271 | - |
dc.identifier.epage | 276 | - |
dc.publisher.place | United States | - |