Automatic Road Pavement Assessment with Image Processing: Review and Comparison

Figure 13

The comparison of the similarity coefficients between GaMM and Morph. The purple axes correspond to the five sets of tested images. For the first set that corresponds to real images with no illumination problems, the results are mixed whereas, for the four other sets, GaMM is the best. The mean of this criterion is 0.6 (variance = 0.0257) for GaMM whereas it is 0.49 (variance = 0.0750) for Morph. However, this method has one step of characterization of the cracks (not introduced in GaMM), and this step can remove cracks that do not respect the characteristics of a cracks (in length, size, and shape). This step contributes to reduce errors, but, in some difficult cases, it decreases the performances of the detection, compared to GaMM.