@inproceedings{a7189dd8301740cc99983dc3cc7c6da6,

title = "Edge detection using fine-grained parallelism in VLSI",

abstract = "This paper demonstrates an optimal time algorithm and architecture for edge detection in real time using fine grained parallelism. Given an image in the form of a two-dimensional array of pixels, this algorithm computes the Sobel and Laplacian operators for skimming lines in the image and then generates the Hough array using thresholding. Hough transforms for M different angles of projection are obtained in a fully systolic manner without using any multiplication or division. An implementation of the algorithm on the MGAP - a fine-grained processor array architecture being developed at the Pennsylvania State University, is shown which computes at the rate of approximately 75,000 Hough transforms per second on a 256 × 256 image using a 25 MHz clock. It is also shown that the algorithm can be easily extended to general case of Radon transforms.",

author = "Chetana Nagendra and Manjit Borah and Mohan Vishwanath and Owens, {Robert M.} and Irwin, {Mary Jane}",

year = "1993",

language = "English (US)",

isbn = "0780309464",

series = "Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing",

publisher = "Publ by IEEE",

pages = "I--401--I--404",

booktitle = "Plenary, Special, Audio, Underwater Acoustics, VLSI, Neural Networks",

note = "1993 IEEE International Conference on Acoustics, Speech and Signal Processing ; Conference date: 27-04-1993 Through 30-04-1993",

}