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Recognition experiments have been performed on handprinted characters using a set of features which has not been applied previously to handprinting. Glucksman's "characteristic loci" were utilized in experiments with the well-known Highleyman data, as well as samples generated at Stanford Research Institute and Honeywell. Two recognition algorithms were tested. Results on numeric samples compare favorably with those of other investigators despite the small dimensionality of the feature vector. On the constrained Honeywell samples, recognition rates exceeding 98 percent were achieved using the simpler algorithm. With alphabetic samples, some problems remain in resolving persistent ambiguities, and methods for attacking these problems are considered.