We proposed a high speed feature extraction algorithm and developed a feature vector extraction chip for high speed character recognition. It is hard to implement a high speed OCR by software alone with statistical method . Thus, the whole recognition process is divided into functional steps, then pipeline processed so that high speed processing is possible with temporal parallelism of the steps. In this paper we discuss the feature extraction step of the functional steps. To extract feature vector, a character image is normalized to 40$\times$40 pixels. Then, it is divided into 5$\times$5 subregions and 4x4 subregions to construct 41 overlapped subregions(10x10 pixels). It requires to execute more than 500 commands to extract a feature vector of a subregion by software. The proposed algorithm, however, requires only 10 cycles since it can extract a feature vector of a columm of subregion in one cycle with array structure. Thus, it is possible to process 12.000 characters per second with the proposed algorithm. The chip is implemented using EPLD and the effectiveness is proved by developing an OCR using it.
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