Navigation on Hand-Crafted Map via Deformation-Tolerant Feature Matching with Google Maps

Non-rigid deformation presents a significant challenge in image processing, as most existing techniques excel only under affine transformations but perform poorly when handling complex deformations, such as stretching, bending, or other irregular distortions. This paper addresses this challenge by introducing a robust pipeline for precise image comparison under non-rigid deformation. We combine image simplification, connectivity recovery, and thinning to preserve structural integrity. The preprocessing phase reduces noise and enhances edges, while the Douglas-Peucker algorithm simplifies the data. AKAZE descriptors and FLANN-based matching, optimized with Lowe's ratio test, are used for accurate feature matching.