Algorithms for hardware-based pattern recognition

  • Authors:

  • Volker Lohweg;Carsten Diederichs;Dietmar Müller

  • Affiliations:

  • Koenig & Bauer AG (KBA), Bielefeld, Westring, Leopoldshööhe, Germany;Koenig & Bauer AG (KBA), Bielefeld, Westring, Leopoldshööhe, Germany;Circuit and System Design Group, Technical University of Chemnitz, Chemnitz, Germany

  • Venue:
  • EURASIP Journal on Applied Signal Processing
  • Year:
  • 2004

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Abstract

Nonlinear spatial transforms and fuzzy pattern classification with unimodal potential functions are established in signal processing. They have proved to be excellent tools in feature extraction and classification. In this paper, we will present a hardware-accelerated image processing and classification system which is implemented on one field-programmable gate array (FPGA). Non-linear discrete circular transforms generate a feature vector. The features are analyzed by a fuzzy classifier. This principle can be used for feature extraction, pattern recognition, and classification tasks. Implementation in radix-2 structures is possible, allowing fast calculations with a computational complexity of O(N)up to O(N ċ ld(N)). Furthermore, the pattern separability properties of these transforms are better than those achieved with the well-known method based on the power spectrum of the Fourier Transform, or on several other transforms. Using different signal flow structures, the transforms can be adapted to different image and signal processing applications.