HIGH-SPEED IMAGE FEATURE DETECTION USING FPGA IMPLEMENTATION OF FAST ALGORITHM

Marek Kraft, Adam Schmidt, Andrzej Kasiński

Abstract

Many of contemporary computer and machine vision applications require finding of corresponding points across multiple images. To that goal, among many features, the most commonly used are corner points. Corners are formed by two or more edges, and mark the boundaries of objects or boundaries between distinctive object parts. This makes corners the feature points that used in a wide range of tasks. Therefore, numerous corner detectors with different properties have been developed. In this paper, we present a complete FPGA architecture implementing corer detection. This architecture is based on the FAST algorithm. The proposed solution is capable of processing the incoming image data with the speed of hundreds of frames per second for a 512×512, 8-bit gray-scale image. The speed is comparable to the results achieved by top-of-the-shelf general purpose processors. However, the use of inexpensive FPGA allows to cut costs, power consumption and to reduce the footprint of a complete system solution. The paper includes also a brief description of the implemented algorithm, resource usage summary, resulting images, as well as block diagrams of the described architecture.

References

  1. Deriche, R. and Giraudon, G. (1993). A computational approach for corner and vertex detection. International Journal of Computer Vision, 10(2):101-124.
  2. Harris, C. and Stephens, M. (1988). A combined corner and edge detection. In Proceedings of The Fourth Alvey Vision Conference, pages 147-151.
  3. Kitchen, L. and Rosenfeld, A. (1982). Gray level corner detection. Pattern Recognition Letters, 1(2):95-102.
  4. Kraft, M. and KasiÁski, A. (2007). Morphological edge detection algorithm and its hardware implementation. In Advances in Soft Computing, Computer Recognition Systems 2 - CORES 2007: 5th International Conference on Computer Recognition Systems, volume 45, pages 132-139.
  5. Mokhtarian, F. and Suomela, R. (1998). Robust image corner detection through curvature scale space. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(12):1376-1381.
  6. Moravec, H. (1979). Visual mapping by a robot rover. In Proceedings of the 6th International Joint Conference on Artificial Intelligence, pages 599-601.
  7. Rosten, E. and Drummond, T. (2005). Fusing points and lines for high performance tracking. In IEEE International Conference on Computer Vision, volume 2, pages 1508-1511.
  8. Rosten, E. and Drummond, T. (2006). Machine learning for high-speed corner detection. In European Conference on Computer Vision, volume 1, pages 430-443.
  9. Smith, S. M. and Brady, J. M. (1997). Susan - a new approach to low level image processing. International Journal of Computer Vision, 23(1):45-78.
  10. Torres-Huitzil, C. and Arias-Estrada, M. (2000). An fpga architecture for high speed edge and corner detection. In CAMP 7800: Proceedings of the Fifth IEEE International Workshop on Computer Architectures for Machine Perception (CAMP'00), page 112, Washington, DC, USA. IEEE Computer Society.
  11. Tsai, D. (1997). Boundary-based corner detection using neural networks. Pattern Recognition, 30(1):85-97.
  12. Wang, H. and Brady, M. (1995). Real-time corner detection algorithm for motion estimation. Image Vision Comput., 13(9):695-703.
Download


Paper Citation


in Harvard Style

Kraft M., Schmidt A. and Kasiński A. (2008). HIGH-SPEED IMAGE FEATURE DETECTION USING FPGA IMPLEMENTATION OF FAST ALGORITHM . In Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008) ISBN 978-989-8111-21-0, pages 174-179. DOI: 10.5220/0001080801740179


in Bibtex Style

@conference{visapp08,
author={Marek Kraft and Adam Schmidt and Andrzej Kasiński},
title={HIGH-SPEED IMAGE FEATURE DETECTION USING FPGA IMPLEMENTATION OF FAST ALGORITHM},
booktitle={Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)},
year={2008},
pages={174-179},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001080801740179},
isbn={978-989-8111-21-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)
TI - HIGH-SPEED IMAGE FEATURE DETECTION USING FPGA IMPLEMENTATION OF FAST ALGORITHM
SN - 978-989-8111-21-0
AU - Kraft M.
AU - Schmidt A.
AU - Kasiński A.
PY - 2008
SP - 174
EP - 179
DO - 10.5220/0001080801740179