• Anatomy & Biological Anthropology
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• v.31 no.4
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• pp.121-131
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• 2018

Stature is one of the unique biological properties of a person, which can be used for identification of the individual. In this regard, statures are estimated for the unknown victims from crimes and disasters. However, the accuracy of estimates may be compromised by inappropriate methodologies and/or practices of stature estimation. Discussed in this study are the methodological issues related to the current practices of forensic anthropological stature estimation in Korea, followed by suggestions to enhance the accuracy of the stature estimates. Summaries of forensic anthropological examinations for 560 skeletal remains, which were conducted at the National Forensic Service (NFS), were reviewed. Mr. Yoo Byung-eun's case is utilized as an example of the NFS's practices. To estimate Mr. Yoo's stature, Trotter's (1970) femur equation was applied even though the fibula equation of a lower standard error was available. In his case report, the standard error associated with the equation (${\pm}3.8cm$) was interpreted as an 'error range', which gave a hasty impression that the prediction interval is that narrow. Also, stature shrinkage by aging was not considered, so the estimated stature in Mr. Yoo's case report should be regarded as his maximum living stature, rather than his stature-at-death. Lastly, applying Trotter's (1970) White female equations to Korean female remains is likely to underestimate their statures. The anatomical method will enhance the accuracy of stature estimates. However, in cases that the anatomical method is not feasible, the mathematical method based on Korean samples should be considered. Since 1980's, effort has been made to generate stature estimation equations using Korean samples. Applying the equations based on Korean samples to Korean skeletal remains will enhance the accuracy of the stature estimates, which will eventually increase the likelihood of successful identification of the unknowns.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1353-1369
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• 2023

In the event of a disaster accident at sea, the scale of damage will vary due to weather effects such as wind, currents, and tidal waves, and it is obligatory to minimize the scale of damage by establishing appropriate control plans through quick on-site identification. In particular, it is difficult to identify pollutants that exist in a thin film at sea surface due to their relatively low viscosity and surface tension among pollutants discharged into the sea. Therefore, this study aims to develop an algorithm to detect suspended pollutants on the sea surface in RGB images using imaging equipment that can be easily used in the field, and to evaluate the performance of the algorithm using input data obtained from actual waters. The developed algorithm uses image enhancement techniques to improve the contrast between the intensity values of pollutants and general sea surfaces, and through histogram analysis, the background threshold is found,suspended solids other than pollutants are removed, and finally pollutants are classified. In this study, a real sea test using substitute materials was performed to evaluate the performance of the developed algorithm, and most of the suspended marine pollutants were detected, but the false detection area occurred in places with strong waves. However, the detection results are about three times better than the detection method using a single threshold in the existing algorithm. Through the results of this R&D, it is expected to be useful for on-site control response activities by detecting suspended marine pollutants that were difficult to identify with the naked eye at existing sites.