Extraction of slant character candidates from maps using circular templates

The paper proposes a method for extracting slant characters from complicated background figures efficiently and rapidly. In this method, slant character candidates are extracted using the black pixel density features, that is, matching rate of two different sized circular templates, which are inscribing and circumscribing a target character, with an original image. In order to estimate performance of the proposed method, the method was applied to 41 topographic map images (512/spl times/512 pixels) involving 1032 slant characters. As a result, the average number of character candidates per character was reduced to about 41 candidates, and 94.3% of 1032 slant characters were extracted correctly.