An automatic thresholding algorithm based on an illumination-independent contrast measure

An automatic and dynamic thresholding algorithm based on an illumination-independent contrast measure is proposed. In this algorithm, a local threshold is calculated for each segmented square region in an image. Since the thresholds obtained in regions that include no characters or objects would produce only noise by thresholding, they are modified by regionwise interpolation based on the contrast measure. The contrast measure is introduced by an illumination reflectance image formation model proposed by T.G. Stockham (1972) where the gray-level function is expressed as the product of an illumination component and a reflectance component. The contrast measure is expressed by the ratio of the standard derivation to the mean of the object reflectance. It is found that, if the illumination function is smooth, the ratio can be calculated from just an image function and the characteristics of the video camera without knowing about the shape of the illumination function. The characteristics are determined for two types of video cameras. The experimental results using 100 outdoor scene images for each camera show that (1) almost all the characters included in the images successfully binarized with the same parameters by this method; (2) this algorithm is independent of character or object size and its gray-level values; (3) the contrast measure is approximately independent of illumination; and (4) this method is applicable to real-world scene images