Adaptive character extraction from continuous handwriting Chinese textbased on classifying between-stroke gaps
Shilong Zhang · Information technology newsletter · 2005
It is prerequisite to extract character from the continuous handwriting Chinese text for its recognition. The paper proposes a novel approach to adaptively extracting character from the continuous handwriting Chinese text based on classification of stroke-between gaps. It first calculates horizontal gaps between strokes in ink, and classifies them into two classes using histogram analysis to extract strokes belonging to the same text line. Then, the strokes belonging to the same line are processed to extract characters. It is adaptive to size of characters using histogram analysis to classify between-stroke gaps. The classification of strokes terminates when their width to height ratio is smaller than a threshold. Many applications show that the approach is effective and robust for character extraction from continuous handwriting Chinese text.