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Prediction of demographic characteristics of a person from handwriting is an upcoming new area of research as previous research mainly focused on the recognition of characters, words or paragraph. Predicting demographic characteristics like age, gender, handedness, nationality and many more can aid in applications like bank cheque processing, document forgery systems etc. The research on prediction of mood from handwriting lacks somewhere and its research can help in medical line to check the stress level of the person. Since there is no detailed survey on this so, this paper presents a detailed literature on the datasets, feature extraction and selection, and classification techniques. It is observed that CNN, hybrid CNN-RNN, SVM, Random Forest and many more gave good results for the classification. The future challenges in this research area are proposed.

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A Survey on Datasets, Feature Extraction and Classification Techniques Used in Personality Classification from Handwriting

  • 会议论文

  • 发表日期：

    2025年

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  • Parul Garg,
  • Naresh Kumar Garg

摘要

Prediction of demographic characteristics of a person from handwriting is an upcoming new area of research as previous research mainly focused on the recognition of characters, words or paragraph. Predicting demographic characteristics like age, gender, handedness, nationality and many more can aid in applications like bank cheque processing, document forgery systems etc. The research on prediction of mood from handwriting lacks somewhere and its research can help in medical line to check the stress level of the person. Since there is no detailed survey on this so, this paper presents a detailed literature on the datasets, feature extraction and selection, and classification techniques. It is observed that CNN, hybrid CNN-RNN, SVM, Random Forest and many more gave good results for the classification. The future challenges in this research area are proposed.