On-line chinese character recognition with effective candidate radical and candidate character selections

Abstract A useful property of Chinese characters is that most of them possess a radical with a meaning. Our system is motivated by this characteristic found in Chinese characters which leads us to radical-based candidate selection approaches, performed before similarity measurement. The searching ranges of the radicals and the characters can be basically decided by the number of strokes in the input script. From the recognized possible radicals, the candidate characters are limited to those having such radicals and those having no radical. Since some of the candidate radicals may have very high matching costs, we can reduce the recognition time by discarding those unlikely candidate radicals. Furthermore, to speed up the inspection of radicals, we developed a radical extraction algorithm to narrow down the searching scope of the reference templates. The radical extraction algorithm was further improved by eliminating false extracted radicals. With these mechanisms, the number of candidate radicals screened out is 286 out of 726 radical templates and the number of candidate characters to be detailed matched is 123 out of 5401 Chinese characters. Through these efforts, the recognition rate improves to be 96.35% for the first rank and 98.96% for the first 10 result candidates with the speed of 0.427 seconds on average per character on a PC using Intel 386-33 CPU.