Fingerprint identification method based on density chart model
A fingerprint recognition and density map technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve problems such as application obstacles, unsatisfactory improvement effects, and large storage space.
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[0182] Our invention can be implemented on ordinary PC computers, and there is no requirement for the operating system.
[0183] The fingerprint recognition algorithm based on multi-features is described in detail below. The main steps in the feature extraction stage include: effective area extraction, direction field estimation, image processing and enhancement, minutiae point extraction, and density map feature extraction; the main steps in the feature comparison or recognition stage include: minutiae point comparison, density map comparison, Decision Fusion. Among them, each step of effective area extraction, direction field estimation, image processing and enhancement, minutiae extraction and minutiae comparison can be carried out by traditional methods. Each step is introduced one by one below. Refer to Figure 1 for the overall flow chart, and Figure 2 introduces the results of each part of the entire process through a specific example.
[0184] Feature extraction:
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