Fourier Descriptors Based on Chain Code Extraction

This paper presents an approach for image boundary reconstruction using Fourier descriptors based on chain code extraction and inverse Fourier transform. The method involves extracting the boundary chain code representation of an image contour, converting it to Fourier domain descriptors through Discrete Fourier Transform (DFT), and then reconstructing the boundary by applying inverse Fourier transform. This technique enables more accurate restoration of image details and shapes, thereby improving the quality of image reconstruction. The implementation typically includes steps such as boundary tracking algorithms (e.g., Moore-neighborhood tracing) for chain code extraction, Fourier coefficient calculation using FFT algorithms, and selective coefficient filtering for noise reduction. Further research can optimize this process by exploring different chain code extraction algorithms (such as Freeman chain codes with 4 or 8 directions) or applying additional image processing techniques to enhance Fourier descriptor accuracy. These improvements can continuously refine image reconstruction methodologies to meet evolving requirements and enhance image processing effectiveness.