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Turk J Elec Engin, VOL.9, NO.1 2001, c TUBITAK Combining Multiple Representations for Pen-based

Summary: Turk J Elec Engin, VOL.9, NO.1 2001, c T¨UBITAK
Combining Multiple Representations for Pen-based
Handwritten Digit Recognition
Department of Computer Engineering
Bogazi¸ci University,
TR-80815, Istanbul-TURKEY
We investigate techniques to combine multiple representations of a handwritten digit to increase
classification accuracy without significantly increasing system complexity or recognition time. In pen-based
recognition, the input is the dynamic movement of the pentip over the pressure sensitive tablet. There
is also the image formed as a result of this movement. On a real-world database of handwritten digits
containing more than 11,000 handwritten digits, we notice that the two multi-layer perceptron (MLP)
based classifiers using these representations make errors on different patterns implying that a suitable
combination of the two would lead to higher accuracy. We implement and compare voting, mixture of
experts, stacking and cascading. Combining the two MLP classifiers we indeed get higher accuracy because
the two classifiers/representations fail on different patterns. We especially advocate multistage cascading
scheme where the second costlier image-based classifier is employed only in a small percentage of cases.
1. Introduction
Handwritten character recognition has attracted enormous scientific interest due to its evident practical


Source: Alpaydın, Ethem - Department of Computer Engineering, Bogaziçi University


Collections: Computer Technologies and Information Sciences