## Abstract

This paper demonstrates an optimal time, fully systolic algorithm for edge detection on a mesh connected processor array. It uses only inexpensive addition and comparison operations which makes it ideal for fine grained parallelism in VLSI. Given an N × N image in the form of a two-dimensional array of pixels, our algorithm computes the Sobel and Laplacian operators for skimming lines in the image and then generates the Hough array using thresholding. The Hough transforms for M different angles of projection are obtained in a fully systolic manner in O(M + N) time, which is asymptotically optimal. In comparison, a previously published multiplication free algorithm has a time complexity of O(NM). An implementation of our algorithm on a mesh connected fine-grained processor array is discussed, which computes at the rate of approximately 170,000 Hough transforms per second using a 50 MHz clock.

Original language | English (US) |
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Pages (from-to) | 67-75 |

Number of pages | 9 |

Journal | Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology |

Volume | 13 |

Issue number | 1 |

DOIs | |

State | Published - Jan 1 1996 |

## All Science Journal Classification (ASJC) codes

- Signal Processing
- Information Systems
- Electrical and Electronic Engineering