A Summary of the Quantitative and Statistical Application Methods of Handwriting Identification
Handwriting identification is a crucial aspect of forensic analysis that heavily relies on the experience of forensic handwriting examiners.Over the years,the increasing demands for accurate identification led to a growing interest in statistical methods within the field.These statistical techniques provided an objective way to quantify the characteristics of handwriting and analyzed the collected data in a reasonable manner.By employing effective statistical methods,not only can the identification conclusions obtained from handwriting analysis be supported by a strong theoretical foundation,but it also allows a deeper exploration of the intricate information hidden within the complex data.This paper aims to provide a comprehensive review of the principles,applications,and recent advancements of several widely used statistical methods in the quantification of handwriting features and the processing of feature data.These statistical methods offered valuable tools for objectively measuring various aspects of handwriting.By utilizing these techniques,forensic handwriting examiners could extract quantitative measurements that serve as valuable evidence in the identification process.In recent years,machine learning had been developed to recognize and classify handwriting patterns,improving the efficiency and accuracy of the identification process.Looking ahead,statistical methods will continue to play a vital role in the field of handwriting identification.In conclusion,the integration of statistical methods in handwriting identification had brought significant advancements to the field.These methods provided an objective and systematic approach to quantifying and analyzing the characteristics of handwriting,thereby supporting the conclusions drawn from handwriting analysis.As technology continues to evolve,it is expected that statistical methods will continue to evolve as well,leading to more accurate and efficient identification processes in the future.
国家科技期刊平台
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