Fast Screening Algorithm for Rotation and Scale Invariant Template Matching

TL;DR

This paper introduces a fast, pre-processing algorithm for template matching that efficiently rules out unlikely regions, effectively handling rotation and scale variations with minimal computational effort.

Contribution

The paper proposes a novel pre-screening method using an octagonal-star-shaped template and inclusion-exclusion principle to accelerate template matching for rotated and scaled images.

Findings

Significantly reduces search space in template matching

Effectively handles arbitrary rotation and scaling

Maintains accuracy without missing the best match

Abstract

This paper presents a generic pre-processor for expediting conventional template matching techniques. Instead of locating the best matched patch in the reference image to a query template via exhaustive search, the proposed algorithm rules out regions with no possible matches with minimum computational efforts. While working on simple patch features, such as mean, variance and gradient, the fast pre-screening is highly discriminative. Its computational efficiency is gained by using a novel octagonal-star-shaped template and the inclusion-exclusion principle to extract and compare patch features. Moreover, it can handle arbitrary rotation and scaling of reference images effectively. Extensive experiments demonstrate that the proposed algorithm greatly reduces the search space while never missing the best match.