Phase-Based Local Features

We introduce a new type of local feature based on the phase and amplitude responses of complex-valued steerable filters. The design of this local feature is motivated by a desire to obtain feature vectors which are semi-invariant under common image deformations, yet distinctive enough to provide useful identity information. A recent proposal for such local features involves combining differential invariants to particular image deformations, such as rotation. Our approach differs in that we consider a wider class of image deformations, including the addition of noise, along with both global and local brightness variations. We use steerable filters to make the feature robust to rotation. And we exploit the fact that phase data is often locally stable with respect to scale changes, noise, and common brightness changes. We provide empirical results comparing our local feature with one based on differential invariants. The results show that our phase-based local feature leads to better performance when dealing with common illumination changes and 2-D rotation, while giving comparable effects in terms of scale changes.