The efficiency of holistic template matching in the recognition of unconstrained handwritten digits

Summary Psychological evidence suggests that simple visual patterns can be recognized by the use of internal representations as holistic templates, but the efficiency of holistic template matching in the recognition of real-life patterns, such as handwritten characters, has been doubted. To clarify this issue, we measured the efficiency of holistic template matching in machine recognition of totally unconstrained handwritten digits. Our learning and recognition algorithm was simple; no previous knowledge of handwritten digits was presupposed, and preprocessing was limited to Gaussian smoothing and normalization with respect to position, size, and orientation. For patterns presented in a known orientation, recognition rates were .69, .77, and .88, respectively, when about 5, 10, or 50 templates had been learned for each type of digit. For patterns presented in unknown orientations, recognition rates were slightly lower. High levels of reliability could be attained by the discounting of classifications based on weak evidence. Apparently, in high reliability recognition, holistic template matching can be used as a first operation by which recognition is achieved for most of the handwritten digits that are seen in real life.