A new feature extraction method from dental X-ray images for human identification

Faranak Shamsafar
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引用次数: 11

Abstract

Using dental radiography is an alternative approach to identify a deceased person, especially in cases that other biometric traits cannot be handled. This paper proposes a new method for feature extraction from dental radiography images to identify people. First, dental works are segmented in the X-ray images using image processing techniques. Then, radius vector function and support function are extracted for each segmented region. These functions are independent of image translation. The presented algorithm modifies both functions to be invariant under image rotation as well. Also, by normalizing the functions, the problems due to image scale variations can be solved. Image translation, rotation and scale variations are basic challenges when dental features are compared in spatial domain. Experiments prove suitable recognition accuracy in the proposed approach which does not require teeth alignment at the matching level.
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一种用于人体识别的牙齿x射线图像特征提取新方法
使用牙科x线摄影是识别死者的另一种方法,特别是在其他生物特征无法处理的情况下。本文提出了一种从口腔放射成像图像中提取特征以识别人的新方法。首先,利用图像处理技术对x射线图像进行分割。然后,对每个分割区域提取半径向量函数和支持函数。这些功能与图像翻译无关。该算法还使这两个函数在图像旋转下保持不变。此外,通过对函数进行归一化,可以解决由于图像尺度变化引起的问题。图像平移、旋转和尺度变化是在空间域比较牙齿特征时面临的基本挑战。实验证明,该方法不需要在匹配层面对牙齿进行对齐,具有较好的识别精度。
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