Abstract
This paper relates to a practical headline area extraction method employing a half-cosine function wavelet network. The half-cosine function wavelet network has multi-level structure. In each level, basis functions with same support width corresponding to a space frequency are arranged. Generally basis functions corresponding to a headline area are wide support width. Therefore, after decomposing an image to weighted basis functions, headline area is obtained by combining support areas of basis functions having high weights in the lower level which has the highest weight. In this paper, we demonstrate the adaptive headline area extractions from Japanese and English documents and video in which the font size of headline changes dynamically. Extraction speed more than 10 fps for video images is achieved. The validity of the proposed method is discussed through experimental results.
