Chinese Journal of Liquid Crystals and Displays, Volume. 40, Issue 5, 796(2025)
Full-surface imaging of rotary workpieces based on adaptive brightness correction
Due to the unique geometric characteristics and dimensional constraints of gold-plated rotary workpieces, it is challenging to quickly and accurately capture their full-surface images. To address these issues, a novel full-surface imaging method based on adaptive brightness correction is proposed. Firstly, to recover information in low-brightness regions, an adaptive brightness adjustment algorithm is introduced. This algorithm initially applies global brightness mapping for pre-adjustment, followed by guided filtering instead of traditional Gaussian filtering to enhance local contrast across multiple scales while preserving features such as scratches and edges. Secondly, an innovative image stitching method based on adaptive Region of Interest (ROI) cropping is designed, which utilizes threshold segmentation in the HSV color space and homography estimation to accurately extract valid regions from the input images. This approach minimizes influence of surface projection distortion and parallax during image fusion and improves computational efficiency. Experimental results show that the brightness correction algorithm improves the quality of image features, leading to a reduction of approximately 50% in the average back-projection error during registration, with image stitching speeds reaching 1.25 frame/s. Compared with classic algorithms like Autostitch and LPC, the proposed method demonstrates notable advantages in both accuracy and efficiency. The proposed method is suitable for acquiring full-surface images and detecting defects on rotational workpieces in industrial environments.
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Bin LIU, Qian LIU, Weiwei MING, Xiaojin HUANG. Full-surface imaging of rotary workpieces based on adaptive brightness correction[J]. Chinese Journal of Liquid Crystals and Displays, 2025, 40(5): 796
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Received: Oct. 28, 2024
Accepted: --
Published Online: Jun. 18, 2025
The Author Email: Qian LIU (liuqianblue@126.com)