11. A method for recognizing handwritten characters using predetermined patterns, comprising: generating the plurality of predetermined patterns, wherein the plurality of predetermined patterns are generated by performing one or more feature extraction operations on the character sample utilizing a Gabor filter, wherein the plurality of predetermined patterns are stored in a memory; acquiring an online handwritten character; pre-processing the online handwritten character; extracting features of the online handwritten character, thereby determining a feature vector, wherein extracting features of the online handwritten character to determine the feature vector comprises: extracting directional features based on the direction of the character sample's points; generating directional pattern images based on the directional features; filtering the directional pattern images using a Gabor filter; and forming the feature vector based on the filtered directional pattern images; generating, using a statistical algorithm, one or more patterns for the online handwritten character based on the feature vector; classifying the online handwritten character, comprising determining a character corresponding to the online handwritten character based on the generated one or more patterns and the plurality of predetermined patterns.
11. A method for recognizing handwritten characters using predetermined patterns, comprising: generating the plurality of predetermined patterns, wherein the plurality of predetermined patterns are generated by performing one or more feature extraction operations on the character sample utilizing a Gabor filter, wherein the plurality of predetermined patterns are stored in a memory; acquiring an online handwritten character; pre-processing the online handwritten character; extracting features of the online handwritten character, thereby determining a feature vector, wherein extracting features of the online handwritten character to determine the feature vector comprises: extracting directional features based on the direction of the character sample's points; generating directional pattern images based on the directional features; filtering the directional pattern images using a Gabor filter; and forming the feature vector based on the filtered directional pattern images; generating, using a statistical algorithm, one or more patterns for the online handwritten character based on the feature vector; classifying the online handwritten character, comprising determining a character corresponding to the online handwritten character based on the generated one or more patterns and the plurality of predetermined patterns. 13. The method of claim 11 , wherein said generating the plurality of predetermined patterns comprises: performing one or more pre-processing operations on a character sample; performing one or more feature extraction operations on the character sample, wherein the one or more feature extraction operations produce a feature vector for the character sample, wherein said performing the one or more feature extraction operations utilizes a Gabor filter; performing statistical training to generate patterns based on the feature vector of the character sample; storing the plurality of predetermined patterns in the memory, wherein the plurality of predetermined patterns are configured to be used to recognize handwritten characters.