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Berkant Savas
Analyses and Tests of Handwritten Digit Recognition Algorithms
This report is a masters thesis written at the Department of
Mathematics, Linköping University. Two different classification
algorithms for handwritten digit recognition have been thoroughly
analysed. The first algorithm uses Higher Order Singular Value
Decomposition (HOSVD) of the training digits. The second algorithm
relies on a specific distance measure, which is invariant to different
transformations, called Tangent Distance (TD). This algorithm was
modified in the implementation part by the use of numerical
derivatives and an approximation of the blurring operator. Two more
classification algorithms were constructed by combining the first two
algorithms. All constructed algorithms have been tested with good
performance for some of them. The best results were achieved by the
Tangent Distance classifier with an error rate of 3%. Finally the
results of a few other classifiers are presented and compared with the
test results obtained in this report.
Sidansvarig: karin.johansson@liu.se
Senast uppdaterad: 2019-12-03