Recognition of Relatively Small Handwritten Characters or "Size Matters"

Abstract

Shape-based online handwriting recognition suffers on small characters, in which the distortions and variations are often commensurate in size with the characters themselves. This problem is emphasized in settings where characters may have widely different sizes and there is no absolute scale. We propose methods that use size information to adjust shape-based classification to take this phenomenon appropriately into account. These methods may be thought of as a pre-classification in a size-based feature space and are general in nature, avoiding hand-tuned heuristics based on particular characters.