Use of automated quality assessment algorithms in fingermark detection research - Application to IND/Zn vs DFO

When developing detection techniques for fingermarks, the detected fingermarks must be evaluated for their quality to assess the effectiveness of the new method. It is a common practice to compare the performance of the new (optimized) technique with the traditional or well-established ones. In current practice, this evaluation step is carried out by a group of human assessors. A new approach is applied in this paper and consists of using algorithms to perform this task. To implement this approach, the comparison between IND/Zn and DFO has been chosen because it has already been the subject of many articles published in recent years and a consensus exists on the superiority of IND/Zn over DFO. The quality of 3'600 fingermarks developed using both detection techniques was assessed automatically using two algorithms: LQM (Latent Quality Metric) and ILFQM (Improved Latent Fingerprint Quality Metric). The distribution of quality scores was studied for both detection techniques. The results showed that fingermarks detected with IND/Zn received higher scores on average than fingermarks detected with DFO, which is in line with the consensus in the literature based on human assessment. The results of this research are promising and shows that automated fingermark quality assessment is an efficient and viable way to comparatively assess fingermark detection techniques.