A FAST Extreme Illumination Robust Feature in Affine Space

Robust feature plays an important role in many vision based applications. This paper proposes a fast extreme illumination robust feature in affine space. It inherits the techniques of extreme point location and main orientation computation from SIFT (Scale Invariant Feature Transform) algorithm, and adopts the rotation and scale invariant circular binary pattern based histograms in the affine space to generate feature vectors of the extreme points. Based on the binary pattern based histograms, this work maximally improves the illumination robustness in affine space and reduces the processing time. Comparing with the typical work-ASIFT(Affine SIFT) that is characterized by strong robustness on the aspects of viewpoint, scale, rotation and illumination, this work improves the robustness for the extreme illumination change in the affine space while maintains the comparable detection performance on the other aspects, and achieves the average 82.6 times improvement on the processing time.