Shuang Kang1, Yinchao He1,2, Wenwen Li1,*, Sen Liu2
CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 933-949, 2024, DOI:10.32604/cmc.2024.056614
- 15 October 2024
Abstract To address the issues of low accuracy and high false positive rate in traditional Otsu algorithm for defect detection on infrared images of wind turbine blades (WTB), this paper proposes a technique that combines morphological image enhancement with an improved Otsu algorithm. First, mathematical morphology’s differential multi-scale white and black top-hat operations are applied to enhance the image. The algorithm employs entropy as the objective function to guide the iteration process of image enhancement, selecting appropriate structural element scales to execute differential multi-scale white and black top-hat transformations, effectively enhancing the detail features of defect… More >