Abstract
Biometric identification is largely dependent on feature extraction technology. As feature extraction techniques are increasingly mature, scholars have gradually turned their attention to the relevant problems between biometric characteristics. This paper reviews the characteristic extraction method of face and fingerprint analyzes the feature classification extraction method based on empirical knowledge and the depth learning-based computer logic sampling extraction method and compares existing solutions from the angle of image processing. Based on feature extraction, it will have prospected in the future biometric identification model of progress.
Highlights
Deep learning has an excellent performance in data analysis and accuracy and has gradually attracted the attention of various industries, and traditional biometric algorithms have been challenged [1]
Scholars have invested in the fields of multi-biological modal identification based on machine learning/deep learning, and have achieved gratifying results in a relatively short period
The third method of identity authentication came into being, that is, automatic identity authentication based on a person's unique physiological or behavioral characteristics, which is collectively referred to as biometric identification technology
Summary
Deep learning has an excellent performance in data analysis and accuracy and has gradually attracted the attention of various industries, and traditional biometric algorithms have been challenged [1]. In contrast to the history of the development of biometric recognition, the processing of biometric images has always been the focus of scholars' research and the aid of computer equipment This process includes the steps of extraction and analysis of relevant biological characteristics and comparison with existing data, and outputs the recognition results. The third method of identity authentication came into being, that is, automatic identity authentication based on a person's unique physiological or behavioral characteristics, which is collectively referred to as biometric identification technology. Behavioral characteristics are formed with acquired habits, including voice, handwriting, gait, and vein structure Such characteristics are stable over a while but have the potential to change over time. The completeness and accuracy of feature extraction are directly related to the recognition accuracy and robustness of the biometric system
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