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A Fingerprint Quality Evaluation Method Based on Visual Cognition Machine Learning of Line Quality Experts

A quality evaluation and machine learning technology, applied in the acquisition/organization of fingerprints/palmprints, instruments, computer parts, etc., which can solve the problems of fingerprint image quality evaluation that is not easy to quantitatively describe, and fingerprint image quality evaluation is incomplete.

Active Publication Date: 2022-02-18
张威 +1
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Problems solved by technology

[0005] In view of the above-mentioned quality evaluation problems of imprinted fingerprint images, to overcome the incomplete evaluation of fingerprint image quality by existing standardization organizations such as NIST, and to use artificial intelligence related methods to learn the basis and feelings of fingerprint identification experts who are not easy to quantitatively describe the quality evaluation of fingerprint images, Quickly, comprehensively and comprehensively give the comprehensive quality of fingerprint images

Method used

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  • A Fingerprint Quality Evaluation Method Based on Visual Cognition Machine Learning of Line Quality Experts
  • A Fingerprint Quality Evaluation Method Based on Visual Cognition Machine Learning of Line Quality Experts
  • A Fingerprint Quality Evaluation Method Based on Visual Cognition Machine Learning of Line Quality Experts

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Embodiment Construction

[0089] The present invention will be further described in detail below in conjunction with the examples.

[0090] Such as figure 1 As shown, the method includes the following steps:

[0091] Step S01: Reconstruction of the leftover area of ​​ridges on the extracted data

[0092] This step conducts dynamic big data sampling analysis and information mining on the information stored in the existing Automatic Fingerprint Identification System (AFIS) database of the forensic science department, and obtains data that can dynamically and objectively reflect "comparison of multi-genre algorithms" and "most fingerprint experts". "Visual inspection and identification" of the local ridge image of the printed fingerprint and the "double-cusp quality requirements" of the printed fingerprint specific area ridge image, as the next step, provide the data source for fingerprint experts to carry out visual cognitive marking.

[0093] Step S01.1: The data to be extracted mainly include:

[00...

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Abstract

The invention relates to a fingerprint quality evaluation method based on ridge quality expert visual cognition machine learning. Including: expert cognition and quality marking of the image quality level of stamping lines in the "on-site reconstruction area of ​​fingerprint line leftover positions", and "expert individual quality evaluation stability analysis" and "expert quality evaluation" for quality marking data. Pattern cluster analysis" and get the priority of each expert's quality marking data; cut the expert's quality marking data into pieces, and use them for image quality evaluation neural network model training according to the priority. Construct and train the neural network model until it evaluates the quality of local blocks and reaches the set accuracy threshold. Using the local block quality evaluation data made by the neural network model, the global comprehensive quality evaluation of the imprinted fingerprint image is calculated. The invention takes into account the bicuspid requirements of "multi-genre fingerprint comparison algorithm" and "expert fingerprint identification" on fingerprint quality, and is widely applicable to image quality evaluation of heterogeneous fingerprints of various specifications.

Description

technical field [0001] The invention provides a fingerprint quality evaluation method based on machine learning of ridge quality experts' visual cognition, which belongs to the field of biometric identification, can be used for multi-comparison algorithm architecture, data quality control of ultra-large-scale fingerprint systems, and can be optimized and compared in AFIS system The risk analysis of missing checks, the targeting range of missed checks, and the evaluation of the practical application value of various heterogeneous fingerprint image data (such as immigration, ID card, driver, examinee fingerprint registration, etc.) in the field of forensic science are of outstanding significance. Background technique [0002] Compared with other biometric identification technologies, fingerprint automatic identification technology has excellent accuracy and high economic practicability, and the current application prospect is very clear. The purpose of building the fingerprint...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06V10/762G06V40/12
CPCG06T7/0002G06T2207/20084G06T2207/20081G06T2207/20021G06T2207/30168G06V40/1347G06V40/13G06V40/1365G06F18/23213
Inventor 张威王威
Owner 张威
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