Pattern identification system

A pattern identification system comprising memory means for storing a plurality of standard column pattern data each calculated based on covariance matrix of a set of column pattern components of a two-dimensional pattern known to belong a corresponding one of each of a plurality of categories and a plurality of standard row pattern data each calculated based on covariance matrix of a set of row pattern components of the two-dimensional pattern;

• calculation means for obtaining a column covariance matrix data representing covariance matrix of a set of column pattern components of a two-dimensional input pattern and a row column covariance matrix data representing covariance matrix of a set of row pattern components of the two-dimensional input pattern;
• multiplier-adder means for multiplying and summing the column covariance matrix data corresponding to the standard and input column pattern components to obtain column multiply-sum data and multiplying and summing the row covariance matrix data corresponding to the standard and input row pattern components to obtain row multiply-sum data;
• means for multiplying the column multiply-sum data and the row multiply-sum data, respectively, to obtain product data;
• detecting means for detecting a product data repesenting a maximum from the product data obtained by the multiplying means with respect to all categories;
• and identification means for identifying the two-dimensional input pattern as belonging to the category represented by the maximum product data detected by the detection means.

A pattern identification system for identifying an input pattern constituted by m number of column pattern components and n number of row pattern components, compring an input pattern covariance matrix calculation unit including m number of n-bit shift registers for storing m number of column pattern component data corresponding to the column pattern components, n number of m-bit shift registers for storing n number of row pattern component data corresponding to the row pattern components, a column covariance matrix calculation circuit for receiving at a time two column pattern component data from the n-bit shift registers so as to obtain covariance matrix of the two column pattern component data, a row covariance matrix calculation circuit for receiving at a time two row pattern component data from the m-bit shift registers so as to obtain covariance matrix of the two row pattern component data, and memory means for storing the column and row covariance matrix data obtained by teh column and row covariance matrix calculation circuits;

• and a similarity calculation unit including memory means for storing a plurality of standard column pattern covariance matrix data each calculated based on covariance matrix of column pattern components known to belong to the corresponding one of the categories and a plurality of standard row pattern covariance matrix data each calculated based on covariance matrix of row pattern components, column multiplier-adder means for multiplying and summing the column covariance matrix data read out from the memory means of the input pattern covariance matrix calculation unit and each standard column pattern covariance matrix data, row multiplier-adder means for multiplying and summing the row covariance matrix data read out from the memory means of the input pattern covariance matrix calculation unit and each standard row pattern covariance matrix data, multiplier means for multiplying the output data of the column and row multiplier-adder means so as to obtain product data, detection means for detecting the largest of the product data obtained by the multiplier means, and identifying means for identifying the input pattern as belonging to the category represented by the largest product data detected by the detection means.