.png){kind=icon}
返回
Machine Learning for Fingerprint Ridge Counting
.png){kind=icon}
PRE
AI
DOI：10.1109/TBIOM.2025.3608616.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Ridge counting is an important feature in standardized fingerprint templates, supporting interoperability, improving matching accuracy, and providing a transparent and interpretable measure to validate automated decisions. However, traditional ridge counting techniques that rely on binarization and skeletonization are prone to artifacts, limiting their accuracy and robustness. In this study, we propose and analyze machine learning methods for ridge counting based on different architectures paradigms such as fully connect residual networks, convolutional and Transformer techniques, which operate directly on raw grayscale fingerprint images. As part of this study, we introduce a benchmark dataset comprising 23,724 of manually annotated ridge counts from 50 subjects. Our experiments show that convolutional and Transformer-based models achieved the highest accuracy, with exact ridge count match rates of 96.6% and 95.6%, respectively, outperforming classical techniques and a commercial solution top ranked in the National Institute of Standards and Technology (NIST) Minutiae Interoperability Exchange (MINEX) III evaluation. Additionally, we investigate the influence of ridge counting on fingerprint matching performance using the Fingerprint Verification Competition 2002 DB1 A (FVC2002) benchmark, with additional cross-dataset tests on Fingerprint Verification Competition 2004 DB1 A (FVC2004) and NIST Special Database 301A (SD301). The source codes, ridge count dataset, and trained models are available on https://github.com/Bonacim/ridge-count.
Keyword:
Fingerprint recognition
Biometrics
Machine learning
Benchmark testing
Standards
NIST
Accuracy
Transformers
Image matching
Training
Ridge counting
fingerprint recognition
machine learning
interpretable biometrics
期刊
I
IF:
0
论文数:
67
被引数:
0
机构
引用论文
Fingerprint classitication based on extraction and analysis of singularities and pseudo ridges.png)
PATTERN RECOGNITION
PATTERN RECOGNITIONIF7.6
PREAI
分享收藏
分享收藏分享收藏分享收藏
查看更多内容