Stroke-order-free on-line Chinese character recognition by stroke adjustment of two-layer bipartite weighted matching

Abstract Dynamic programming (DP) is good at recognizing on-line standard-stroke-order Chinese characters. We propose a two-stage bipartite weighted matching to rearrange the stroke order of a test on-line Chinese handwriting before recognition. At the first layer, for each stroke pair which matches one stroke in the test handwriting with one stroke in the reference character, we generate a stroke-based vector graph (SVG) and the bipartite weighted matching determines the best stroke permutation of the handwriting, stroke-based matched vector graph (SMVG), from the SVG. At the second layer, we superimpose all SMVGs to form a character-based vector graph (CVG), and the bipartite weighted matching calculates the final stroke mapping between the test handwriting and the reference character. Experimental results reveal that the modified split-and-merge DP matching using the stroke adjustment method recognizes on-line stroke-order-varied handwritings with accuracy 89%, much higher than accuracy 5.2% for the original split-and-merge DP matching.