{"title":"Real-time NIR camera brightness control using face detection","authors":"J. Vugrin, S. Lončarić","doi":"10.1080/00051144.2023.2203554","DOIUrl":null,"url":null,"abstract":"The face image analysis field is a well-established research area in computer vision and image processing. An important requirement for accurate face image analysis is a high-quality input face image. In different real-life scenarios, however, the face is often not properly illuminated, which makes the face analysis very difficult or impossible to accomplish. Although a better performance is obtained by changing the spectrum from visible to near-infrared, it is still not enough for extreme illumination conditions. To obtain a high-quality near-infrared face image, a fast automatic brightness control method using approximate face region detection is proposed, which properly adjusts the brightness of the face part of the image. A novel algorithm for approximate face region detection based on spatio-temporal sampled skin detection is proposed together with the split-range feedback controller and the face absence handle. The proposed method is much faster than state-of-the-art solutions and accurate in approximate face region detection. The complete execution time is lower than 10 milliseconds which makes it suitable for hard real-time embedded system implementation and usage, while the reference brightness value is achieved within 10–15 frames, making it robust to extreme illumination conditions in a scene.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":"64 1","pages":"593 - 605"},"PeriodicalIF":1.7000,"publicationDate":"2023-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Automatika","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1080/00051144.2023.2203554","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
The face image analysis field is a well-established research area in computer vision and image processing. An important requirement for accurate face image analysis is a high-quality input face image. In different real-life scenarios, however, the face is often not properly illuminated, which makes the face analysis very difficult or impossible to accomplish. Although a better performance is obtained by changing the spectrum from visible to near-infrared, it is still not enough for extreme illumination conditions. To obtain a high-quality near-infrared face image, a fast automatic brightness control method using approximate face region detection is proposed, which properly adjusts the brightness of the face part of the image. A novel algorithm for approximate face region detection based on spatio-temporal sampled skin detection is proposed together with the split-range feedback controller and the face absence handle. The proposed method is much faster than state-of-the-art solutions and accurate in approximate face region detection. The complete execution time is lower than 10 milliseconds which makes it suitable for hard real-time embedded system implementation and usage, while the reference brightness value is achieved within 10–15 frames, making it robust to extreme illumination conditions in a scene.
AutomatikaAUTOMATION & CONTROL SYSTEMS-ENGINEERING, ELECTRICAL & ELECTRONIC
CiteScore
4.00
自引率
5.30%
发文量
65
审稿时长
4.5 months
期刊介绍:
AUTOMATIKA – Journal for Control, Measurement, Electronics, Computing and Communications is an international scientific journal that publishes scientific and professional papers in the field of automatic control, robotics, measurements, electronics, computing, communications and related areas. Click here for full Focus & Scope.
AUTOMATIKA is published since 1960, and since 1991 by KoREMA - Croatian Society for Communications, Computing, Electronics, Measurement and Control, Member of IMEKO and IFAC.