This paper presented quite a number of different experiments to compare it to other state of the art algorithm and also to show a variety of applications for their algorithm. I found this to be a strength and a weakness. A common mistake that authors will make is to not substantiate their claims well enough with both theoretical and experimental analysis. In the form of experimental analysis, papers may fall short in a number of ways. One problem is if the paper does not present an adequate set of experiments. A second problem may be that the paper simply does not analyze and comment on the experiments provided. This paper presented a number of experiments that seem to conclude that the algorithm presented was good. The experiments ranged over a number of different applications and compared against a number of different algorithms. However, the paper did a poor job of actually explaining the experiments, the results and the implications of the results. For example, in the trademark retrieval experiment the paper states that:

“It has been manually verified that no visually similar trademark has been missed by the algorithm.”

All though this test is a start, it does not compare their algorithm to other existing algorithms and it does not state what the implications of the statement above are. I question how good of a metric this experiment is since the statement above implies that the metric was to have the potential infringer in the top choices (not necessarily the top choice) and also does not take into account false positives.