METHOD FOR DETERMINING ATTRIBUTE USING NEURAL NETWORK AND FUZZY LOGIC

An attribute decision method includes steps of making a comparison between one feature value, selected from seven feature values, of an input pattern contained in an input image and membership functions determined from 37 standard patterns including alphanumeric characters of "0" to "9" and "A" to "Z" and a hyphen of "-" with respect to the selected feature value and then obtaining output values of the membership functions for the individual standard patterns with respect to the input pattern. The seven feature values are, when the input pattern is a mesh pattern, vertical structure vector sums, horizontal structure vector sums, up-down and left-right area differences, and a vertical cross number. The method also includes steps of calculating a total value of the output value for the feature value for each of the standard patterns, and determining a standard pattern of the highest total value among the calculated total values and thus deciding one of the standard patterns which has the highest similarity to the input pattern.