Capturing Character Contours from Images of Ancient Chinese Calligraphy

novel methodology is proposed to capture character contours from images of ancient Chinese calligraphy which mainly includes two steps: feature points detecting from character contours and contour segment approximating. A new feature-point-detection method called PCACSS (principle component analysis based curvature scale space) is thus proposed. Compared with several existing methods for feature-point-detection, it is robust to noise and can accurately detect feature points from character contours automatically. With feature points determined by PCACSS, the character contours are divided into some contour segments, each contour segment is then approximated with a straight line or Bezier curve depending on the least square error. The proposed method has been implemented and tested on a wide variety of calligraphy images. Resultant outline fonts captured from calligraphy images with our method are visual pleasing as demonstrated by the examples shown in this paper.