Interference Fringe Processing with Filtering, Binarization, and Skeletonization for Fringe Spacing Calculation

This interference fringe processing program implements a comprehensive pipeline including filtering, binarization, and skeletonization operations. The implementation begins with filtering applied to the interference fringe pattern to eliminate noise and suppress unnecessary details, typically using Gaussian or median filters to preserve fringe edges while reducing high-frequency artifacts. Subsequently, the processed image undergoes binarization using thresholding techniques (such as Otsu's method or adaptive thresholding) to convert the grayscale image into a binary black-and-white representation, facilitating subsequent morphological operations. The binarized image then undergoes skeletonization through thinning algorithms (like Zhang-Suen or Guo-Hall methods) to extract the primary fringe contours while maintaining topological connectivity. Finally, the skeletonized image is processed to generate a refined single-pixel-width representation through iterative pruning and endpoint detection, enabling precise calculation of fringe spacing using pixel-counting or distance transform approaches. Throughout this implementation, we preserve essential processing steps and algorithmic concepts while expanding technical descriptions to clarify the computational methodology.