Pattern Matching and Analysis of Drawn or Handwritten Digits Using Correlation

The recognition of drawn digits is a challenging task in the field of image processing and pattern recognition. A drawn or handwritten digits recognition system using correlation matching algorithm for digits recognition and k-neighbor classifying algorithm to select the true digit. Database includes handwritten digit examples which are collected from a hundred persons. These digit images converted to binary type before added to the database. The proposed system will aid applications for postal/parcel digits recognition and conversion of any hand written document into structural text form. In this proposed system first image acquisition or drawn digits then input image is segmented into isolated digits by assigning a number to each digit using a labeling process. The features of the digits that are crucial for classifying them at recognition stage are extracted.
Digit images converted to binary and using correlation matching algorithm for digits recognition and k-neighbor classifying algorithm to select the true digit.