Dorothea Blostein
Professor, School of Computing at Queen's University in Kingston, Ontario.

Address
Dorothea Blostein
School of Computing
Goodwin Hall 720
Queen's University
Kingston, Ontario, Canada
K7L 2N8
(613) 533-6537
blostein@cs.queensu.ca

Dr. Blostein received computer science degrees from the University of Illinois (B.Sc. in 1978, Ph.D. in 1987) and Carnegie Mellon University (M.Sc. in 1980). Since 1988 she has been a faculty member in the School of Computing at Queen's University.

Table of contents for this web page
New Research Area: Biomechanics and Adaptive Tensegrity
Research in Graphics Recognition and Document Classification
Ongoing Projects to Develop Tensegrity Software
Graduate Student Supervision
Undergraduate Student Supervision
Teaching

New Research Area: Biomechanics and Adaptive Tensegrity

Fascia, also called connective tissue, forms a bodywide network that provides structural support, protection, shock absorption and elastic recoil (Fascia: The Tensional Network of The Human Body, Elsevier, 2012; Fascia Research Society) . Fascial tissue exhibits a great diversity of characteristics, ranging from stiff cable-like structures such as tendons to supple sheets such as the superficial fascia under the skin. Fascia is adaptive, changing characteristics in response to the demands placed on it.

Tensegrity (tensional integrity) is a structural principle developed by Kenneth Snelson and Buckminster Fuller. In a tensegrity structure, isolated components under compression are held in place by a network of components under tension. The dynamic interplay of tension and compression forces makes tensegrity structures strong and flexible. Biotensegrity modeling researchers include Tom Flemons, Graham Scarr, and Steve Levin (The Levin Biotensegrity Archive).

My research interests are as follows.

Research in Graphics Recognition and Document Classification

Dr. Blostein has a long-standing research program in pattern recognition, document analysis, and document classification. The main research goal is to smooth the interface between paper and electronic versions of documents. Dr. Blostein and her students have worked on developing computer technology to read, write, and edit diagram notations such as music notation, math notation, maps, schematics, and architectural drawings. The text portions of scanned documents can be analyzed with OCR (Optical Character Recognition), but further processing is required to extract the information contained in diagram notations. Dr. Blostein and her students investigate the use of techniques such as graph transformation and tree transformation, in order to construct an interpretation of the 2D arrangement of symbols in a diagram. Other projects include classification of documents (applied to biomedical documents and software engineering documents), and the use of internet searches to validate document recognition results.
Of special interest to Dr. Blostein is exploration and exploitation of the relationship between diagram recognition and diagram generation. Technology for generation is far ahead of technology for recognition: diagram generation software outperforms diagram recognition software; speech generation outperforms speech understanding; computer graphics is ahead of computer vision.

Dr. Blostein is coauthor of the Lime Music Notation Software. Both Macintosh and IBM PC versions are available for free trial use.

Dr. Blostein was a plenary speaker at CICM 2009. She was Chair of GREC2001, the Fourth IAPR International Workshop on Graphics Recognition, Kingston, Ontario, in September, 2001.

Classification and Mining of Software Engineering Documents

Classification of Biomedical Documents

Holographic Reduced Representations

Formulating and Evaluating Recognition Algorithms using the Recognition Strategy Language

Validation and Performance Evaluation of Document Recognition Algorithms

Surveys on Topics in Diagram Recognition and Document Classification

Recognition of Mathematics Notation Using Tree Transformation

Graph Transformation and Application to Diagram Recognition

Lime Music Notation Software

Computer Vision



Research Supervision

Tensegrity Simulation Projects

Extensions to the NASA Tensegrity Robotics Toolkit, Sept. 2015 to April 2016

Creating Tensegrity Structures in ArtiSynth January-April 2016 Extensions to the NASA Tensegrity Robotics Toolkit, May-August 2016

Theses Supervised

Undergraduate Projects and Research Assistants

Teaching

Current Courses
CISC 859 Pattern Recognition. Fall 2014, 2013, 2011, 2008 and previous years
CISC 324 Operating Systems. Winter 2016, 2015, 2014, 2013, 2012, 2009 and previous years

Other Courses I have Taught
CISC 365 Algorithms I. Fall 2010. Also Winter 2003 and previous years.
CISC 124 Introduction to Computing Science II. Fall 2002.
    Here is Java image manipulation code used in this course. This code can be used as a starting point by anyone wishing to write image manipulations in Java.

CISC 352 Artificial Intelligence. Fall 2003.
CISC 221 and CISC 231. Computer Architecture. Winter 1997 and previous years.