Advancements in Gurmukhi Handwriting Analysis: Machine Learning Approaches for Attribute Classification

Aarti Pandey Kaur

doi:10.36948/ijfmr.2026.v08i01.69110

Advancements in Gurmukhi Handwriting Analysis: Machine Learning Approaches for Attribute Classification

Author(s)	Ms. Aarti Pandey Kaur
Country	India
Abstract	Handwriting analysis has broad applications in fields such as forensics, biometrics, and psychological profiling. This study investigates the classification of age, gender, and handedness from handwritten Punjabi documents using three machine learning approaches: k-Nearest Neighbors (KNN), Support Vector Machine (SVM), and a hybrid SVM-KNN model. A novel dataset comprising over 500 handwritten samples collected from 100+ individuals was created, with features extracted using advanced techniques including Histogram of Oriented Gradients (HOG), Speeded-Up Robust Features (SURF), Scale-Invariant Feature Transform (SIFT), Oriented Gradient Descriptors (OGD), and wavelet transforms. The models were evaluated based on classification accuracy, and results showed that while KNN provided a reliable baseline, SVM outperformed it by better capturing nonlinear relationships in the data. The hybrid SVM-KNN model achieved the highest overall performance, with accuracies of 79% for age, 80% for gender, and 78% for handedness classification, demonstrating its effectiveness in handling complex class overlaps. These findings underscore the importance of combining machine learning models to enhance predictive accuracy and establish a strong foundation for future studies in handwriting attribute analysis.
Keywords	kNN, SVM, SURF, COLD, HOG, SIFT, OGD
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 1, January-February 2026
Published On	2026-02-27
DOI	https://doi.org/10.36948/ijfmr.2026.v08i01.69110

View / Download PDF File

E-ISSN 2582-2160

doi

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads

Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 8 Isu 2 Cover Page Vol 8 Isu 1 Cover Page Vol 7 Isu 6

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9687-828-838	editor@ijfmr.com

International Journal For Multidisciplinary Research

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Advancements in Gurmukhi Handwriting Analysis: Machine Learning Approaches for Attribute Classification

Share this