By Richard Suchenwirth, Jun Guo, Irmfried Hartmann, Georg Hincha, Manfred Krause, Zheng Zhang
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Any two neighbouring sub-sequences must have different values. 5-4) where N5 is the number of sub-sequences, W is the number of white pixels, B is the number of black pixels and e is a threshold. When a defective edge is detected, it is smoothed out. lf the number of white pixels is lass than the number of black pixels, all white pixels are replaced with black pixels; otherwise black pixels are replaced with white pixels. Fti;. 1 Principles of Feature Extraction Feature extraction is one of the crucial stages in all pattern recognition systems.
4-2). This prevents the Suppression ofthin lines and reduces the influence of inhomogenaus lighting. Let s(i,j) be the grayscale image of a character with N rows and M columns. 5 Edge Smoothing on Binary Patterns ln the binary image of printed Chinese characters, there are often a Iot of defects on some edges of strokes, especially the horizontal and vertical strokes (see examples in fig. 5-1). g. the SDF feature), making them rather unstable. When such features are used, preprocessing must include edge smoothing.
4-3 Structure of the TECH/S recognition system recognition sottware. See [McC 87] for a recent overview of alphanumeric OCR systems that are available in the market. A prototype Kanji OCR system is described in [Hir 80]. Fig. 4-3 shows the rough structure of the experimental TECHIS system developed by the authors at the Technical University of Berlin. lf optical recognition of Chinese characters is to be used in real-life applications, the input technology must allow the reading of at least one page, or even better an opening (two facing pages), in one exposition.