Robert K. Powalka

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Dynamic (on-line) cursive script recognition works with data obtained from a digitising device which contains temporal information regarding the order of writing. In such a system the data is processed as entered, or immediately afterwards. Direct feedback can be provided to the user. Users of interactive dynamic recognition systems can adjust their writing(More)
Word shape information can be helpful in handwriting recognition. It can be used by a segmentation based recognizer to verify the results of the recognition of individual segmented letters. It is often one of the main features used by wholistic recognizers. This paper describes extraction of the word shape information through identification of the middle(More)
Introduction Handwriting recognition can benefit from combining results obtained from different recognizers. Various methods can be employed to combine the results (6). Often such multiple recognizers are used independently. This is usually done without interaction among the recognizers. A question can be raised as to whether any dynamic interaction during(More)
Cursive script has many ambiguities. Feature extraction, by locating some specific characteristics of a writing sample in isolation or in combination with other features, can minimise the effect of these ambiguities. There are many features that can be extracted from any given sample. Information about the expected vertical letter position within the word,(More)
Combining results of multiple approaches to recognizing handwriting is becoming increasingly attractive as a means of improving recognition performance. Most of the reported work concerns combination of results at character level (i.e. letter, digit). This paper concentrates on combination of results at the word level. Two approaches are presented: word(More)