A Review of Feature Extraction Methods for Handwritten Character Recognition | Original Article

ABSTRACT:

This work provides a survey of feature extraction strategies for recognizing segmented (decontextualized) characters when no internet connection is available. Perhaps the most crucial step toward optimal recognition performance in character recognition systems is settling on a suitable feature extraction strategy. Each of the many possible character representations from solid binary characters to character contours to skeletons (thinned characters) to gray-level subimages of each character requires a unique set of feature extraction algorithms. We address the invariance qualities, reconstructability, and predicted distortions and variability of the characters of the various feature extraction approaches. The challenge of knowing which feature extraction technique to use when is also covered. Once a few of interesting feature extraction approaches have been found, they must be experimentally examined to determine which is best for the specific application at hand.