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  • Research Article
  • Open Access

Nearest Neighborhood Grayscale Operator for Hardware-Efficient Microscale Texture Extraction

EURASIP Journal on Advances in Signal Processing20062007:052630

  • Received: 23 November 2005
  • Accepted: 10 September 2006
  • Published:


First-stage feature computation and data rate reduction play a crucial role in an efficient visual information processing system. Hardware-based first stages usually win out where power consumption, dynamic range, and speed are the issue, but have severe limitations with regard to flexibility. In this paper, the local orientation coding (LOC), a nearest neighborhood grayscale operator, is investigated and enhanced for hardware implementation. The features produced by this operator are easy and fast to compute, compress the salient information contained in an image, and lend themselves naturally to various medium-to-high-level postprocessing methods such as texture segmentation, image decomposition, and feature tracking. An image sensor architecture based on the LOC has been elaborated, that combines high dynamic range (HDR) image aquisition, feature computation, and inherent pixel-level ADC in the pixel cells. The mixed-signal design allows for simple readout as digital memory.


  • Information Processing System
  • Hardware Implementation
  • Image Sensor
  • Severe Limitation
  • Visual Information Processing System

Authors’ Affiliations

TU Dresden, Lehrstuhl Hochparallele VLSI-Systeme und Neuromikroelektronik, Helmholtzstraße 10, Dresden, 01062, Germany
TU Kaiserslautern, FB Elektrotechnik und Informationstechnik, Lehrstuhl Integrierte Sensorsysteme, Erwin-Schrödinger-Straße, Kaiserslautern, 67663, Germany


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© C. Mayr and A. König 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.