Issue No. 02 - February (2012 vol. 34)
M. Muehlich , CanControls, Aachen, Germany
D. Friedrich , Inst. of Imaging & Comput. Vision, RWTH Aachen Univ., Aachen, Germany
T. Aach , Inst. of Imaging & Comput. Vision, RWTH Aachen Univ., Aachen, Germany
Image analysis problems such as feature tracking, edge detection, image enhancement, or texture analysis require the detection of multi-oriented patterns which can appear at arbitrary orientations. Direct rotated matched filtering for feature detection is computationally expensive, but can be sped up with steerable filters. So far, steerable filter approaches were limited to only one direction. Many important low-level image features are, however, characterized by more than a single orientation. We therefore present here a framework for efficiently detecting specific multi-oriented patterns with arbitrary orientations in grayscale images. The core idea is to construct multisteerable filters by appropriate combinations of single-steerable filters. We exploit that steerable filters are closed under addition and multiplication. This allows to derive a design guide for multisteerable filters by means of multivariate polynomials. Furthermore, we describe an efficient implementation scheme and discuss the use of weighting functions to reduce angular oscillations. Applications in camera calibration, junction analysis of images from plant roots, and the discrimination of L, T, and X-junctions demonstrate the potential of this approach.
matched filters, filtering theory, image processing, junction analysis, multisteerable matched filters, image analysis, feature tracking, edge detection, image enhancement, texture analysis, multioriented pattern detection, rotated matched filtering, feature detection, steerable filter, multivariate polynomials, angular oscillations, camera calibration, Polynomials, Junctions, Approximation methods, Feature extraction, Correlation, Fourier series, Image edge detection, camera calibration., Steerable filters, feature detection, junction analysis, orientation estimation, rotated matched filtering, multi-oriented patterns, template equation, trigonometric polynomials, multivariate polynomials
D. Friedrich, M. Muehlich and T. Aach, "Design and Implementation of Multisteerable Matched Filters," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 34, no. , pp. 279-291, 2012.