This article examines the criteria for graphological analysis, identifies its parameters, and analyzes each criterion and parameter using handwriting samples, providing conclusions. Special attention is given to the technical equipment and software necessary for graphological expertise, emphasizing their importance. The roles of high-precision microscopes, graphometric devices, digital scanners, and high-precision cameras, which are considered technical support for graphological expertise, are elucidated in the analysis. The functions of artificial intelligence and machine learning models are explained, including automatic handwriting recognition and classification, analysis of biometric characteristics, detection of anomalies and fraud, and data archiving and comparison.
Criteria, Parameters, And Technical And Software Support For Graphological Analysis
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References
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