10. A method in a computer system for generating a position feature probability table for use in recognizing handwritten characters, the method comprising: receiving a plurality of sample handwritten characters, each sample handwritten character representing a character and having a sequence of one or more strokes, each stroke represented by one of a plurality of position features that describe starting and ending coordinates of the stroke; determining for each sample handwritten character a position feature string that represents that character, the position feature string having the position feature of each stroke in the sequence, each of the position features in a position feature sting having a place within the position feature string based on the sequence in which the described stroke was handwritten in the sample handwritten character; for each possible feature distance, each feature distance representing a combined distance between the starting coordinates of a pair of position features and between the ending coordinates of the pair of position features, generating a match count of all occurrences of the feature distance between each pair of position features in all possible pairs of position feature strings in which the pair of position features are at the same place within the pair of position feature strings and in which the pair of position feature strings represent the same character; generating a total count of all occurrences of the feature distance between each pair of position features in all possible pairs of position feature strings in which the pair of position features are at the same place within the pair of position feature strings; calculating a probability value based on the generated match count and the generated total count; and storing the calculated probability value for the feature distance in the position feature probability table, so that the stored probability values can be used to recognize handwritten characters.
10. A method in a computer system for generating a position feature probability table for use in recognizing handwritten characters, the method comprising: receiving a plurality of sample handwritten characters, each sample handwritten character representing a character and having a sequence of one or more strokes, each stroke represented by one of a plurality of position features that describe starting and ending coordinates of the stroke; determining for each sample handwritten character a position feature string that represents that character, the position feature string having the position feature of each stroke in the sequence, each of the position features in a position feature sting having a place within the position feature string based on the sequence in which the described stroke was handwritten in the sample handwritten character; for each possible feature distance, each feature distance representing a combined distance between the starting coordinates of a pair of position features and between the ending coordinates of the pair of position features, generating a match count of all occurrences of the feature distance between each pair of position features in all possible pairs of position feature strings in which the pair of position features are at the same place within the pair of position feature strings and in which the pair of position feature strings represent the same character; generating a total count of all occurrences of the feature distance between each pair of position features in all possible pairs of position feature strings in which the pair of position features are at the same place within the pair of position feature strings; calculating a probability value based on the generated match count and the generated total count; and storing the calculated probability value for the feature distance in the position feature probability table, so that the stored probability values can be used to recognize handwritten characters. 12. The method of claim 10 wherein the probability value is calculated according to the following formula: ##EQU7## where the probability is the generated match count divided by the generated total count.