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A Simple and Novel CBIR Technique for Features Extraction Using AM Dental Radiographs

机译:一种简单新颖的CBIR技术,用于使用AM牙科射线照片进行特征提取

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摘要

Dental image processing is most immerging field for human identification. Dental features remain more or less invariant over time compared to other identification clues like fingerprint, iris, etc. which are not available in some case of major accidents. The purpose of dental image processing is to match the post-mortem (PM) radiograph with the ante mortem (AM) radiograph based on some characteristic or feature of the radiograph for human identification. Image enhancement is necessary because of poor quality and low contrast of dental image at primary stage. Thereafter segmentation algorithms are applied to the enhanced dental x-ray image which helps to find two major regions namely gap valley and tooth isolation. The main crucial part is tooth and feature extraction of dental image. In this paper, we propose a simple and novel CBIR technique to extract individual tooth and thereafter we extract geometrical features of dental x-ray radiographs for human identification purpose. We compared feature vectors of database with query image and calculated the distance vector for matching purpose.
机译:牙科图像处理是人类识别的最沉浸领域。与其他识别线索(如指纹,虹膜等)相比,牙齿特征随时间变化或多或少保持不变,而在某些重大事故中,这些线索是不可用的。牙齿图像处理的目的是根据人体X射线照片的某些特征将验尸X射线照片与验尸X射线照片进行匹配。图像增强是必需的,因为在初期牙科图像质量差且对比度低。此后,将分割算法应用于增强的牙科X射线图像,这有助于找到两个主要区域,即间隙谷和牙齿隔离。主要的关键部分是牙齿图像的牙齿和特征提取。在本文中,我们提出了一种简单新颖的CBIR技术来提取单个牙齿,然后我们提取牙科X射线照片的几何特征以供人类识别。我们将数据库的特征向量与查询图像进行比较,并计算出距离向量以进行匹配。

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