Showing papers on "Handwriting recognition published in 1982"
TL;DR: An online handwritten character recognition algorithm, suitable for the home use computer, was developed, which recognizes a quickly written multi-stroke character using dynamic programming based pattern matching technique.
Abstract: An online handwritten character recognition algorithm, suitable for the home use computer, was developed. A character, written on a digitizing tablet, is expressed as a directional angle sequence. In order to recognize a quickly written multi-stroke character, the character pattern is converted into a single interconnected stroke pattern. The recognition is carried out using dynamic programming based pattern matching technique.
63 citations
TL;DR: The Viterbi algorithm and a modified trellis incorporating a pertinent statistics of distorted patterns are used and this method was applied to recognition of handwritten English letters and Japanese Katakana's with success.
Abstract: In this paper a new recognition system of distorted patterns is presented, where the Viterbi algorithm and a modified trellis incorporating a pertinent statistics of distorted patterns are used. The system works in a manner quite similar to our own human decision process. The trellis is so constructed that it can eliminate all the irrelevant pattern classes at the outset and leave only the most probable for its fimal decision, yielding a great economy of processing time and the accuracy of decision. The method was applied to recognition of handwritten English letters and Japanese Katakana's with success. The method is also universal and can be applied to any category of distorted pattems.
19 citations
01 May 1982
TL;DR: A method using models with fuzzy primitives which can, by utilizing the knowledge about the universe and the context of the primitives, correct possible errors in primitive recognition and therefore improve the ability of the recognition system.
Abstract: In structural pattern recognition, the errors in primitive recognition have an important effect on the recognition rate of object. This paper proposes a method using models with fuzzy primitives. It provides a simple and effective approach which can, by utilizing the knowledge about the universe and the context of the primitives, correct possible errors in primitive recognition and therefore improve the ability of the recognition system. In order to apply this method to the on line recognition of handwritten chinese ideographs, a method for feature extraction of graphisms, i.e. MLG method, is developed. Our system is implemented on a micro-computer Apple-II, the experiments for 200 chinese ideographs give satisfactory results.