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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