Chinese Journal of Liquid Crystals and Displays, Volume. 38, Issue 5, 617(2023)

Real-time automatic image cropping based on portrait detection

Yu-hang WU1, Shan-ling LIN1,3、*, Zhi-xian LIN1,2,3, and Tai-liang GUO2,3
Author Affiliations
  • 1School of Advanced Manufacturing,Fuzhou University,Quanzhou 362200,China
  • 2School of Physics and Information Engineering,Fuzhou University,Fuzhou 350116,China
  • 3China Fujian Photoelectric Information Science and Technology Innovation Laboratory,Fuzhou 350116,China
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    In order to solve the problem that the existing automatic image cropping algorithm mistakenly cuts off the whole person or part of the body parts of the main figure, which leads to the missing of the key information of the image and the poor composition of the image, this paper proposes a real-time automatic image cropping method based on portrait detection. This method divides image cropping into two stages: portrait detection and intelligent composition. It aims to take the extracted portrait coordinate information as the input of the intelligent cropping algorithm, and then combines the composition rule based on aesthetics to automatically compose the picture, so as to ensure the integrity of the portrait information in the cropping result and improve the composition beauty of the picture. The experimental results show that the lightweight detection network modified on the basis of Center-Net in this paper reduces the computation amount by 86% and improves the accuracy by 3.34%, which is convenient to apply the cropping algorithm to mobile devices. The FPS of the whole cropping algorithm reaches 77, and the cropped portrait information is complete, and the overall composition of the picture is improved.

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    Yu-hang WU, Shan-ling LIN, Zhi-xian LIN, Tai-liang GUO. Real-time automatic image cropping based on portrait detection[J]. Chinese Journal of Liquid Crystals and Displays, 2023, 38(5): 617

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    Paper Information

    Category: Research Articles

    Received: Aug. 1, 2022

    Accepted: --

    Published Online: Jul. 4, 2023

    The Author Email: Shan-ling LIN (sllin@fzu.edu.cn)

    DOI:10.37188/CJLCD.2022-0258

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