Recognition of cursive text is an active area of research, with recognition rates even lower than that of hand-printed text. Higher rates of recognition of general cursive script will likely not be possible without the use of contextual or grammatical information. For example, recognizing entire words from a dictionary is easier than trying to parse individual characters from script. Reading the Amount line of a check (which is always a written-out number) is an example where using a smaller dictionary can increase recognition rates greatly. The shapes of individual cursive characters themselves simply do not contain enough information to accurately (greater than 98%) recognize all handwritten cursive script.
Recognition of cursive text is an active area of research, with recognition rates even lower tha.n that of hand-printed text. Hig.her rates of recognition of general cursive script will likely not be possible without the use of contextual or grammatical information. For example recognizing entire words from a dictionary is easier than trying to parse individual characters from script Reading the Amount line of a check (which is always a written-out number) ,is an example where using a smaller dictionary can increase recognition rates greatly. The shapes of individual cursive characters themselves simply do not contain enough information to accurately (greater than 98%) recognize all handwritten cursive script