Handwriting match and AI content detection

Hrishikesh Panigrahi; Siddhanth Naidu; Ambuj Pandey; Phiroj Shaikh; Amiya Kumar Tripathy

doi:10.6977/IJoSI.202506_9(3).0005

International Journal of Systematic Innovation ›› 2025, Vol. 9 ›› Issue (3) :75 -95. DOI: 10.6977/IJoSI.202506_9(3).0005

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Handwriting match and AI content detection

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Department of Computer Engineering, Don Bosco Institute of Technology, Mumbai, India

^* phiroj@dbit.in

Hrishikesh Pramod Panigrahi is currently pursuing a Bachelor of Engineering in Computer Engineering at The Bombay Salesian Society’s Don Bosco Institute of Technology, Mumbai University. He has demonstrated strong technical expertise through hands-on experience in backend development, machine learning, and web applications. Hrishikesh has led backend teams, contributed to AI-driven academic integrity tools, and developed innovative mobile and web solutions. His technical proficiency includes programming languages such as Java, GoLang, Python, and Kotlin, and frameworks such as Django, ReactJS, and TensorFlow. He has published a research paper titled “Smart Posture Analyzer For Exercise” at the Institute of Electrical and Electronics Engineering (IEEE). His areas of interest include artificial intelligence, system design, and full-stack development.

Siddhanth Naidu is a Computer Engineering student at The Bombay Salesian Society’s Don Bosco Institute of Technology, Kurla (Mumbai University). He has worked on impactful projects such as FLMS (Flood Location, Management, and Solution), an IEEE-published flood management system, and Dawn of Survival, an Android game developed in Unreal Engine. His technical skills include Java, Spring Boot, Python, ReactJS, HTML/CSS, Unreal Engine, and Unity. He has presented research at the International Conference on IoT, Communication, and Automation Technology (ICACAT) 2023 and was part of the ACM (Aluminum Composite Material) Design Team at Don Bosco Institute of Technology, Kurla. Siddhanth’s interests lie in AI, web development, system design, and game design.

Ambuj Pandey is a Computer Engineering graduate from The Bombay Salesian Society’s Don Bosco Institute of Technology, Kurla (Mumbai University). He has worked on impactful projects such as EDT, Expiry (Expiry Date Tracker, an Android app to track the expiry of purchased groceries), FLMS (an IEEE-published flood management system), and Dawn of Survival (an Android game developed in Unreal Engine) during his college years. His technical skills include C++, Python, Docker, Django, ReactJS, HTML/CSS, and Unreal Engine. He has published a research paper at ICACAT 2023. Ambuj’s interests lie in AI, web development, and game design.

Phiroj Shaikh is currently an Associate Professor at the Department of Computer Engineering, The Bombay Salesian Society’s Don Bosco Institute of Technology, Mumbai, India, affiliated with the University of Mumbai. He earned a PhD degree in Computer Science & Technology (in the domain of Web Data Mining) from Nagpur University, Nagpur, India. He has academic experience of over two decades with more than 60 research publications in journals/conferences. His areas of interest include natural language processing (with a special focus on regional language development), computational linguistics, and algorithm analysis. He is currently focusing on Educational Technology research area. He has been invited as an expert for faculty development programs, as a session expert, and as a reviewer at various conferences.

Amiya Kumar Tripathy is currently a Professor at the Department of Computer Engineering, The Bombay Salesian Society’s Don Bosco Institute of Technology, Mumbai, India, affiliated with the University of Mumbai. He earned a PhD degree in Computer Science & Engineering (in the domain of Data Mining & Wireless Sensor Networks) from the Indian Institute of Technology Bombay, Mumbai, India. He was an adjunct professor at the School of Science, Edith Cowan University (ECU), Australia. He was a visiting researcher at the Rajamangala University of Technology, Bangkok, Thailand, working on Internet of Things (IoT)-enabled remote monitoring for the Precision Agriculture Farming project. He has been in the software industry, research, and academia for more than two decades, having around 150 publications in journals/conference papers. His research focuses on data science, computer vision, remote sensing, and IoT for Precision Agriculture. He has contributed to numerous collaborative research and consultancy projects in the domain of data analytics in India and abroad. He has served on the technical program committees of several international conferences, been invited as a plenary speaker, and co-chaired sessions at various conferences.

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Abstract

Machine-generated text presents a potential threat not only to the public sphere but also to education, where the authenticity of genuine students is compromised by the presence of convincing, synthetic text. There are also concerns about the spread of academic misconduct, particularly direct replication among students. In response to these challenges, this paper introduces the Handwriting Match and Artificial Intelligence (AI) Content Detection System (HMAC). HMAC utilizes optical character recognition (OCR) mechanisms to convert handwritten and typed content from a single-page portable document format into machine-readable text, thus enabling further analysis. Drawing on recent advances in natural language understanding, HMAC aims to preserve the educational value of assignments by effectively detecting AI-generated content. In addition, HMAC has a strong plagiarism detection system that uses a comparative analysis of student submissions in a particular academic field. This paper describes HMAC’s architecture, methodology, and results, emphasizing its key contributions: improved handwritten content extraction with OCR and improved identification of AI-generated content. The study addresses the research question of how HMAC improves the identification of AI-generated content and supports academic integrity compared to other methodologies.

Keywords

Academic Assessment / Artificial Intelligence Content Detection / Document Analysis / Similarity Detection / Transformer-Based Models

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Hrishikesh Panigrahi, Siddhanth Naidu, Ambuj Pandey, Phiroj Shaikh, Amiya Kumar Tripathy. Handwriting match and AI content detection. International Journal of Systematic Innovation, 2025, 9(3): 75-95 DOI:10.6977/IJoSI.202506_9(3).0005

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