There are many instances in which character shape of a class changes smoothly to that of another class. Although there are many ways of the change, the most delicate change is curvature feature. The paper treat this problem systematically in both theoretically and experimentally. Specifically some confusing pairs were constructed which are well known in the field of OCR, such as 2 Z and 4 9. A series of samples generated using each model which change subtly were provided to conduct a psychological experiment. The results exhibit a monotone change of recognition rates from nearly 100% to 0% as the shape changes continuously. To imitate the humans' performance, feature of curvature was extracted based on continuous function representation based on Bezier's spline curve. Specifically two methods were tried from theoretical and engineering points of view and very successful results were obtained.

Handwritten character recognition has been increasing its importance and has been expanding its application areas such as office automation, postal service automation, automatic data entry to computers, etc. It is challenging to develop a handwritten character recognition system with high processing speed, high performance, and high portability, because there is a trade-off among them. In current technology, it is difficult to attain high performance and high processing speed at the same time with single algorithms, and therefore, we need to find an efficient way of combination of multiple algorithms. We present an engineering solution to this problem. The system is based on multi-stage strategy as a whole: The first stage is a simple, fast, and reliable recognition algorithm with low substitution-error rate, and data of high quality are recognized in this stage, whereas sloppily written or degraded data are rejected and sent out to the second stage. The second stage is composed of a sophisticated structural pattern classifier and a pattern matching classifier, and these two complementary algorithms run in parallel (multiple expert approach). We demonstrate the performance of the completed system by experiments using real data.