Orthogonal Polar V Transforms and application to shape retrieval

• We proposed a novel orthogonal rotation-invariant moments (ORIMs) named as PVTs.
• The computation of the PVTs is significantly simpler compared with traditional ORIMs.
• The PVTs achieve very good results in shape retrieval.

The traditional orthogonal moments (e.g., Zernike moments) are formulated with polynomials as their basis that often face the problem of computation difficulty especially with the high-order moments. In this paper, we present a novel set of transforms namely the Polar V Transforms (PVTs). We can use the PVTs not only to generate the rotation-invariant features but also to capture global and local information of images. Since the PVTs basis functions can keep a low order of polynomials, we can significantly speed-up the runtime for computing the kernels. The experimental results have demonstrated that our proposed method outperforms the previous methods in runtimes and achieves very good results in shape retrieval compared to the previous methods especially when the images with high degree of perspective distortions.