Showing papers on "Handwriting recognition published in 1975"

Computer Recognition of Handwritten Numerals by Polygonal Approximations

Abstract: The outlines of handwritten numerals are approximated by polygons using a method previously developed by Pavlidis and Horowitz [10]. This enables a simple evaluation of many intuitively descriptive features for numerals, for example, relative position and type of concave arcs. The method was tested on the Munson data (IEEE Data Base 1.2.2), and an overall error rate of 9.4 percent was achieved without any statistical optimization. A characteristic property of this approach is the existence of two steps: the first step (primitive feature generation) is primarily numerical, and the second step (feature selection and classification) makes extensive use of semantics.

Handwriting synthesis and classification by means of space-variant transform and Karhunen–Loève analysis

Abstract: Optical-pattern-recognition techniques are generally unable to provide an efficient approach to the classification of optical data, because of the linearity of the Fourier transform. A space-variant imaging model is proposed, whose behavior is characterized on the basis of orthonormal polynomials. The optical data are described in an orthonormal space based upon these polynomials. Proper-axis rotation and dimensionality reduction are supplied by the Karhunen–Loeve transform. The intrinsic variables then become available, allowing the clustering of the data (considered as belonging to statistical classes). This work is illustrated by examples of handwriting recognition and classification.