MS ThesisLIBRARY FOR ORGANIZATION OF IMAGE RECOGNITION SYSTEMS
under supervision of Dr. Messner
University of New Hampshire, September, 2002
many recognition problems it is possible to divide the recognition task
into a collection of separate processes. This thesis develops a method
that simplifies the creation of automatic recognition systems. Formal
separation of different algorithm steps was performed and an interface
for communicating between each step was developed. Inorder to evaluate
the robustness of the proposed method, the algorithms developed by Mr.
Tony Pawlak (M.S. UNH ECE 1998) in his thesis work on automatic human
brain cell recognition were implemented. The original human brain cell
recognition research was done using Matlab software. After the original
recognition process was ported into the proposed standard, improvements
were made to demonstrate how the designed system could be extended and
modified. To demonstrate how a "new" recognition task could be
implemented a different recognition problem was chosen: the counting of
bacteria in a pure culture. Documented examples show that the proposed
method and standards simplify the organization, execution, and
maintenance of the recognition procedures. Developed in this thesis is a
ready to use library for various algorithms with examples and
documentation as well as a full discussion on how researchers can
develop their own modules for inclusion.Complete documentation on
standards and interfacing is included in appendices.
DisclaimerCopyright (c) 2002 Alexander Shyrokov
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DownloadsThesis pdf file (2Mb) Mirror
Presentation pdf file (1.5Mb) Mirror
Binaries (Win32, 6Mb) Mirror
Source code (STLport, TIFF lib and samples are not included) (Win32, 1Mb) Mirror
Samples (2.5Mb) Mirror
STLport 4.5 sources (1Mb) Mirror
TIFF lib sources (1Mb) Mirror
Other linksUniversity of New Hampshire
The Synthetic Vision and Pattern Analysis Laboratory
Department of Computer and Electrical Engineering