Double-rotated Matched Filtering

Using the concept of steerable filters, it is possible to represent the rotation of a known template – and thus arbitrary orientations of lines or edges – as a linear combination of a fixed number of base filters, thus allowing a computationally efficient detection of 1D structures. In spite of their usefulness in many image processing areas, such structures exhibit one important drawback: Due to the aperture problem, it is impossible to localize such features in images exactly. Junctions or corners, on the contrary, allow to find exact point matches in image sequences, but existing steerable filter approaches are not capable of modeling such templates. In this paper, we show how to extend rotated matched filtering using steerable filters such that it can represent multioriented image structures. As an example, we examine one special type of double-oriented feature which is especially important for applications like registration or camera calibration: the checkerboard pattern.