Evaluation details.

The application of biometrics has expanded the wings to many domains of application. However, various biometric features are being used in different security systems; the fingerprints have their own merits as it is more distinct. A different algorithm has been discussed earlier to improve the security and analysis of fingerprints to find forged ones, but it has a deficiency in expected performance. A multi-region minutiae depth value (MRMDV) based finger analysis algorithm has been presented to solve this issue. The image that is considered as input has been can be converted into noisy free with the help of median and Gabor filters. Further, the quality of the image is improved by sharpening the image. Second, the preprocessed image has been divided into many tiny images representing various regions. From the regional images, the features of ridge ends, ridge bifurcation, ridge enclosure, ridge dot, and ridge island. The multi-region minutiae depth value (MRMDV) has been computed based on the features which are extracted. The test image which has a similarity to the test image is estimated around MRMDV value towards forgery detection. The MRMDV approach produced noticeable results on forged fingerprint detection accuracy up to 98% with the least time complexity of 12 seconds.

生物识别技术的应用已拓展至众多应用领域。当前不同安全系统中会采用各类生物识别特征，其中指纹因具备更强的独特性而拥有独特优势。此前已有相关算法被提出，用于提升指纹防伪检测与分析的安全性，但这类算法的预期性能存在不足。为此，本文提出一种基于多区域细节点深度值（multi-region minutiae depth value, MRMDV）的指纹分析算法以解决上述问题。所采用的输入图像可通过中值滤波器与Gabor滤波器实现降噪处理，随后通过图像锐化操作进一步提升图像质量。其次，将预处理后的图像分割为多个代表不同区域的子图像，从各区域子图像中提取纹线端点、纹线分叉点、纹线包围点、纹线小点以及纹线岛点等特征。基于所提取的特征计算多区域细节点深度值（MRMDV），通过该值评估待测图像与参考样本的相似度，以此完成伪造指纹检测。所提MRMDV算法在伪造指纹检测任务中表现优异，检测准确率可达98%，且时间复杂度极低，仅需12秒。