Thiagarajar College of Engineering, Madurai, Tamilnadu, India.
J Digit Imaging. 2013 Apr;26(2):259-68. doi: 10.1007/s10278-012-9492-4.
Human identification using dental radiographs is important in biometrics. Dental radiographs are mainly helpful for individual and mass disaster identification. In the 2004 tsunami, dental records were proven as the primary identifier of victims. So, this work aims to produce an automatic person identification system with shape extraction and matching techniques. For shape extraction, the available information is edge details, structural content, salient points derived from contours and surfaces, and statistical moments. Out of all these features, tooth contour information is a suitable choice here because it can provide better matching. This proposed method consists of four stages. The first step is preprocessing. The second one involves integral intensity projection for segmenting upper jaw, lower jaw, and individual tooth separately. Using connected component labeling, shape extraction was done in the third stage. The outputs obtained from the previous stage for some misaligned images are not satisfactory. So, it is improved by fast connected component labeling. The fourth stage is calculating Mahalanobis distance measure as a means of matching dental records. The matching distance observed for this method is comparatively better when it is compared with the semi-automatic contour extraction method which is our earlier work.
利用牙科 X 光片进行人类身份识别在生物识别技术中非常重要。牙科 X 光片主要有助于个体和大规模灾难的身份识别。在 2004 年的海啸中，牙科记录被证明是识别受害者的主要依据。因此，这项工作旨在开发一种具有形状提取和匹配技术的自动人员识别系统。对于形状提取，可用的信息是边缘细节、结构内容、源自轮廓和曲面的显著点以及统计矩。在所有这些特征中，牙齿轮廓信息是一个合适的选择，因为它可以提供更好的匹配。该方法包括四个阶段。第一步是预处理。第二步是对上颚、下颚和单个牙齿进行整体强度投影分割。在第三步中使用连通分量标记进行形状提取。对于一些未对准的图像，前一阶段获得的输出结果并不令人满意。因此，通过快速连通分量标记进行了改进。第四步是计算马氏距离度量作为匹配牙科记录的手段。与我们之前的半自动轮廓提取方法相比，该方法的匹配距离观察结果要好得多。
