Hand-written recognition method based on assembled classifier

Abstract

The invention discloses a method for identifying handwritten Chinese characters based on a combination classifier, which has the advantages that after hand-inputted Chinese characters collected undergo treatments of smoothed filter, noise removal, resampling and data linear normalization, the characters undergo the peeling-off points removal treatment, which removes points of stroke segments which deviate from hand-inputted Chinese characters, which exceed the set threshold value, thereby facilitating the extraction of turning points of strokes and the correct input of stroke segments; setting up basic stroke segment types and corresponding parameter characteristics is to define separating points for separation according to time intervals of sampling points of hand-inputted Chinese characters while sampling; when the directional deviation of a stroke segment is in the range of the set angle threshold, the stroke segment is automatically corrected; a separating connection relation is built, and as for stroke segments which are connected in fact, but separated due to writing habits, the stroke segments are treated as connected stroke segments after being identified, thereby better differentiating a plurality of similar Chinese characters; by calculating Freeman chain codes, hand-inputted Chinese characters can be conveniently identified by using the whole character identification classifier.

Description

technical field [0001] The invention relates to a handwriting recognition processing technology, in particular to a handwriting recognition method based on a combined classifier. Background technique [0002] On May 25, 2005, the Chinese invention patent "Method and System for Handwriting Recognition" (publication number CN 1619583A) discloses a method and system for handwriting recognition, which is especially effective for recognizing ideographic Chinese characters containing multiple strokes. Usually written according to standard order. The method includes receiving a representation of a handwritten input Chinese character written on a user interface of an electronic device, then extracting a directional feature vector and a stroke segment feature vector from the input Chinese character, and comparing the directional feature vector with a model Chinese character to provide a short candidate Chinese character list and the corresponding first confidence score, and then com...

AI Technical Summary

Problems solved by technology

This method can effectively realize the recognition of handwritten input Chinese characters, but after the smoothing, noise deletion and size normalization preprocessing of handwritten input Chinese characters, large errors may occur in the subsequent training and recognition; in the end The design of the classifier used for recognition only considers the stroke segment, and does not adopt other technical means for phenomena such as continuous strokes, writing deformation, and complex font structure, so that there is no good method for dealing with the above situations; in addition, the search method of this method less efficient

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