The Development of an Identification Photo Booth System based on a Deep Learning Automatic Image Capturing Method
With advances in technology, photo booths equipped with automatic capturing systems have gradually replaced the identification (ID) photo service provided by photography studios, thereby enabling consumers to save a considerable amount of time and money. Common automatic capturing systems employ text and voice instructions to guide users in capturing their ID photos; however, the capturing results may not conform to ID photo specifications. To address this issue, this study proposes an ID photo capturing algorithm that can automatically detect facial contours and adjust the size of captured images. The authors adopted a deep learning method (You Only Look Once) to detect the face and applied a semi-automatic annotation technique of facial landmarks to find the lip and chin regions from the facial region. In the experiments, subjects were seated at various distances and heights for testing the performance of the proposed algorithm. The experimental results show that the proposed algorithm can effectively and accurately capture ID photos that satisfy the required specifications.
Document Type: Research Article
Affiliations: 1: Department of Computer Science and Information Engineering, National Quemoy University, Taiwan 2: Department of Electrical Engineering, National Taiwan Ocean University, Taiwan 3: Department of Computer Science and Engineering, National Taiwan Ocean University, Taiwan
Publication date: March 1, 2021
This article was made available online on November 13, 2020 as a Fast Track article with title: "The Development of an Identification Photo Booth System based on a Deep Learning Automatic Image Capturing Method ".
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