A Fast Local Analysis by Thresholding applied to image matching
Résumé
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