After reading the author's rebuttal I have increased the technical quality to 2 and after reading the the other reviews I increased the potential impact to 3. The authors replied to many questions but not to all, in particular the answer was not satisfactory to the question about the parameter K which is one of the crucial parameter in any segmentation algorithm. Why they did not provide the results using the suggested automatic method in Fig4 instead of cyclying on possible (wrong) number of clusters? I would have expected to see in the results the performances with at least one auto-tuning heuristic to asses its generality (at least the one suggested by the authors). In the following the issues found in the paper: 1) In Eq(2) when constructing the adjecency matrix, the ranges of the distances d(...) and \delta(...) are the same? In the line 114 d(s) is a measure of heterogeneity, in line 125 of distance and in Eq(2) of color distance.