C
Ching Y. Suen
Researcher at Concordia University
Publications - 532
Citations - 25017
Ching Y. Suen is an academic researcher from Concordia University. The author has contributed to research in topics: Handwriting recognition & Feature extraction. The author has an hindex of 65, co-authored 511 publications receiving 23594 citations. Previous affiliations of Ching Y. Suen include École de technologie supérieure & Concordia University Wisconsin.
Papers
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Journal ArticleDOI
Parallel image transformation and its VLSI implementation
TL;DR: Several theorems on image transformations have been proved and new algorithms has been proposed to perform the functions mentioned above, which can be very useful to image processing, pattern recognition and related areas, especially real-time applications.
Proceedings ArticleDOI
Cursive script recognition: A fast reader scheme
D. Guillevic,Ching Y. Suen +1 more
TL;DR: A cheque processing system currently under development, based on a psychological model of the reading process for a fast reader, and the module for extracting graphical clues, implemented with the techniques of mathematical morphology, is discussed.
Proceedings ArticleDOI
Associative switch for combining multiple classifiers
TL;DR: A novel combination technique, called an associative switch, is developed for solving the problem of combining multiple classifiers for recognizing totally unconstrained handwritten numerals using a neural net trained by the backpropagation technique with a modified energy criterion.
Journal ArticleDOI
Edge extraction of images by reconstruction using wavelet decomposition details at different resolution levels
TL;DR: A multiresolution-edge extraction with respect to an iterative reconstruction procedure is developed to ameliorate the quality of the reconstructed edges in this case and results in clear final edges of the document images.
Journal ArticleDOI
Automatic Extraction of Baselines and Data From Check Images
Ke Liu,Ching Y. Suen,Mohamed Cheriet,Mohamed Cheriet,J.N. Said,J.N. Said,Christine P. Nadal,Yuan Yan Tang +7 more
TL;DR: A novel approach to extract data from check images is proposed based on the determination of baselines of checks, a priori information about the positions of data on checks, and a layout-driven item extraction method that is effective and performs well.