A Compact System for Real-Time Detection of Line Segments

  • Nozomu Nagata
  • Tsutomu Maruyama
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3617)


In this paper, we describe a compact circuit for real-time detection of line segments using the Line Hough Transform (LHT). The LHT is a technique to find out lines in an image. The LHT is robust to noises, but requires long computation time. The circuit calculates (1) r and θ of lines (r is the distance from the origin to a line and θ is the angle of the line) by the LHT units in parallel, and (2) start and end points of the lines by the other units which are completely pipelined with the LHT units. With this parallel and pipeline processing, the circuit can detects line segments by π/512 angle steps in a standard size image (640 × 480) in real-time. This circuit was implemented on an off-the-shelf PCI board with one Field Programmable Gate Array (FPGA) chip. The size of the circuit is 45% of the chip, which makes it possible to implement other circuits for higher level processing of object recognition on the same chip, or the performance can be improved twice by using the rest of hardware resources.


Line Segment Field Programmable Gate Array Edge Point Pipeline Processing Memory Bank 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Hanahara, K., Maruyama, T., Uchiyama, T.: A real time processor for the Hough transform. IEEE Trans. Pattern. Anal. Mach. Intell. 10, 121–125 (1987)CrossRefGoogle Scholar
  2. 2.
    Rhodes, F.M., Disturi, J.J., Chapman, G.H., Emerson, B.E., Soares, A.M., Raffel, J.I.: A monolithic Hough transform processor based on restructurable VLSI. IEEE Trans. Pattern. Anal. Mach. Intell. 10, 106–110 (1988)CrossRefGoogle Scholar
  3. 3.
    Van Swaaij, M.F.X.D., Catthoor, F.V.M., De Man, H.J.: Deriving ASIC architecture for the Hough Transform. Parallel Computing 16, 113–121 (1990)zbMATHCrossRefGoogle Scholar
  4. 4.
    Atiquzzamau, M.: Pipelined implementation of the multi-resolution Hough Transform in a pyramid multiprocessors. Pattern Recognition Letters, 841–851 (1994)Google Scholar
  5. 5.
    Ben-Tzvi, D., Naqui, A., Sandler, M.: Synchronous multiprocessor implementation of the Hough Transform. In: Computer Vision Graphics Image Process 1990, pp. 437–446 (1990)Google Scholar
  6. 6.
    Choudhary, A.-N., Ponnussary, R.: Implementation and evaluation of Hough transform algorithm on shared-memory multiprocessors. J. Parallel Distributed Comput. 12, 178–188 (1991)CrossRefGoogle Scholar
  7. 7.
    Abbott, A.L., Athanas, P.M., Chen, L., Elliott, R.L.: Finding Lines and Building Pyramids with Splash 2. In: FCCM 1994 (1994)Google Scholar
  8. 8.
    Chung, K.L., Lin, H.Y.: Hough Transform On Reconfigurable Meshes. Computer Vision and Image Processing (2), 278–284 (1995)Google Scholar
  9. 9.
    Nakanishi, M., Ogura, T.: Real-time line extraction using a highly parallel Hough transform board. In: Proceedings of International Conference on Image Processing, pp. 582–585 (1997)Google Scholar
  10. 10.
    Pan, Y., Li, K., Hamdi, M.: An Improved Constant-Time Algorithm for Computing the Radon and Hough Transforms on a Reconfigurable Mesh. IEEE Trans. Systems, Man and Cybernetics-A(29) (4), 417 (1999)Google Scholar
  11. 11.
    Tagzout, S., Achour, K., Djekoune, O.: Hough transform algorithm for FPGA implementation. Signal Processing 81(6), 1295–1301 (2001)zbMATHCrossRefGoogle Scholar
  12. 12.
    Nagata, N., Maruyama, T.: Real-time Detection of Line Segments Using The Line Hough Transform. In: IEEE International Conference on Filed-Programmable Technology, pp. 89–96 (2004)Google Scholar
  13. 13.
  14. 14.

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Nozomu Nagata
    • 1
  • Tsutomu Maruyama
    • 1
  1. 1.Systems and Information EngineeringUniversity of TsukubaTsukuba IbarakiJapan

Personalised recommendations