A Fast Local Analysis by Thresholding applied to image matching

Key structures extraction and matching are key steps in computer vision. Many fields of application need large image acquisition and fast extraction of fine structures. In this study, we focus on situations where existing local feature extractors give not enough satisfying results concerning both accuracy and time processing. Among good illustrations, we can quote short-line extraction in local weakly-contrasted images. We propose a new Fast Local Analysis by threSHolding (FLASH) designed to process large images under hard time constraints. We use “micro-line” points as key feature. These are used for shape reconstruction (like lines) and local signature design. We apply FLASH on the field of concrete infrastructure monitoring where robots and UAVs are more and more used for automated defect detection (like cracks). For large concrete surfaces, there are several hard constraints such as the computational time and the reliability. Results show us that the computations are faster than several existing algorithms in image matching and FLASH has invariance to rotation, partial occlusion, and scale range from 0.7 to 1.4 without scale-space exploration.