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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Proceedings ArticleDOI
Hybrid feature extraction and feature selection for improving recognition accuracy of handwritten numerals
TL;DR: A novel multi-class divergence criterion for large scale feature analysis is proposed and a random feature selection strategy is used to congregate three new hybrid feature sets to improve the recognition accuracy of handwritten numerals.
Journal ArticleDOI
Variable-Length Signature for Near-Duplicate Image Matching
Li Liu,Yue Lu,Ching Y. Suen +2 more
TL;DR: A new visual descriptor, viz., probabilistic center-symmetric local binary pattern, is proposed to characterize the appearance of each image patch, which utilizes the earth mover's distance which is good at handling variable-length signatures.
Journal ArticleDOI
StrCombo : combination of string recognizers
TL;DR: A graph-based approach that regards each segment from individual string recognizers as nodes of a graph, and choose the optimal path with the lowest cost to output a combined result is proposed.
Proceedings ArticleDOI
Text detection from scene images using sparse representation
TL;DR: A sparse representation based method is proposed for text detection from scene images that starts with edge information extracted using Canny operator and then group these edge points into connected components that are labeled as text or non-text by a two-level labeling process.
Proceedings ArticleDOI
Automatic extraction of items from cheque images for payment recognition
TL;DR: A novel approach is proposed for the extraction of legal and courtesy amounts and date from cheque images based on the structural description of cheques and several image processing techniques and algorithms perform well.