快速单曝光高动态范围高反光金属表面缺陷辨识算法研究
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中图分类号：TP391；TG88DOI：10.3969/j.issn.1004-132X.2025.09.016
Research on Rapid Single-exposure HDR Defect Recognition Algorithm for HighlyReflectiveMetal Surfaces
JIA Weihaol² WANG Peng² CHEN KaiTONG FeiWANG Guobiao1.2* 1.School ofMechanical Engineering，TianjinUniversity，Tianjin，300350 2.International Institute for Innovative Design and Intelligent Manufacturing of Tianjin University in Zhejiang，Shaoxing，Zhejiang，312000 3.Ningbo Kono Precision Technology Co.，Ltd.，Ningbo，Zhejiang，315000
Abstract： A rapid single-exposure HDR defect recognition algorithm was proposed for highly reflective metal surfaces. This algorithm was based on detail enhancement techniques and CycleGAN.The input low dynamic range （LDR） images were first converted to HSV color space and processed with guided filtering to obtain luminance and detail layers. The CycleGAN network was then used to enhance the dynamic range of these layers separately. The enhanced luminance and detail layers were weighted and fused， followed by filtering and denoising to produce an HDR image suitable for defect recognition.Defects were identified in the HDR image using threshold segmentation，feature selection，and morphological processing. This single-exposure algorithm was experimentally compared with three classic single-exposure algorithms and one multi-exposure algorithm.The evaluation was based on five metrics：peak signal-to-noise ratio（PSNR），image entropy，processing time，gray histograms，and recognition results. The experimental results indicate that the algorithm herein outperforms three other single-exposure algorithms in effectively addressng overexposure isues，achieving results comparable to multi-exposure algorithms.Additionally，it has a shorter processing time，making it suitable for online detection.Furthermore，this algorithm demonstrates superior capability in extracting image detail information compared to other algorithms， resulting in higher accuracy in recognition.
Key words：highly reflective metal； single-exposure high dynamic range（HDR） imaging；detail en-hancement；cycle-consistent generative adversarial network（CycleGAN）
0 引言
低反光或弱反光表面对视觉观测影响不大，但是具有高反光特性的目标表面反射率高，产生的局部镜面反射光易使工业数字相机采集的图像亮度出现局部过饱和，造成检测盲区，导致被测表面质量信息隐没在周围复杂环境中。（剩余11349字）
