Removing the bias from line detection

The extraction of curvilinear structures is an important low-level operation in computer vision. Most existing operators use a simple model for the line that is to be extracted, i.e., they do not take into account the surroundings of a line. Therefore, they will estimate a wrong line position whenever a line with different lateral contrast is extracted. In contrast, the algorithm proposed in this paper uses an explicit model for lines and their surroundings. By analyzing the scale-space behavior of a model line profile, it is shown how the bias that is induced by asymmetrical lines can be removed. Thus, the algorithm is able to extract an unbiased line position and width, both with sub-pixel accuracy