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Keywords Detection in Handwritten Documents
The long-term aim of this project is to develop techniques and software for the processing of unconstrained handwritten documents. The short terms goals are 1) the enhancement, “de-noising” and removal of artifacts in degraded digital handwritten document images, 2) text-lines and words segmentation independent of scripts or symbols and 3) identification of a small set of keywords in handwritten document images for document classification, retrieval or other purposes.
Faculty Supervisor:
Drs. T.D. Bui and C.Y. Suen
Student:
Mehdi Haji
Partner:
IMDS Software Inc.
Discipline:
Engineering
Sector:
Information and communications technologies
University:
Concordia University
Program:
Accelerate
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