Optimizing Whiteboard Digitization with Clarix: An Automated Vision-Based System for Real-Time Text Extraction and Surface Cleaning

Abstract: Whiteboard digitization in educational settings grapples with challenges posed by handwritten text, mathematical notation, and unstructured layouts that confound traditional Optical Character Recognition (OCR) systems. Clarix, a low-cost embedded system, addresses these issues by integrating a Raspberry Pi, high-resolution camera, and servo-driven erasure mechanism to automate content capture, text extraction, and archiving as searchable PDFs. This study benchmarks five multi-modal Large Language Models (LLMs) (GPT-4o, Claude, Gemini, DeepSeek, Grok) against traditional OCR systems (PaddleOCR, EasyOCR, TesseractOCR) for extracting whiteboard content across mathematics, physics, and economics domains. Results highlight a stark performance divide: multimodal LLMs achieved F1-scores ranging from 0.7550 to 0.8466, with Gemini leading at 0.8466 (precision 0.8188, recall 0.8784), followed by GPT- 4o (F1=0.8162) and DeepSeek (F1=0.7965), while PaddleOCR topped traditional systems with an F1-score of 0.3333 (precision 0.3523, recall 0.3223), followed by EasyOCR (0.1158) and Tesser-actOCR (0.0000). Notably, increased region detection correlated with diminished performance, underscoring the superiority of contextual understanding over exhaustive segmentation. Clarix’s fusion of intelligent automation and advanced text processing marks a transformative advancement in bridging analog and digital educational environments.

Abdellah NABOU, Ameksa Mohammed, Ezzahoud Hajar, Bazgour Yassine and Abouhane Zahra. “Optimizing Whiteboard Digitization with Clarix: An Automated Vision-Based System for Real-Time Text Extraction and Surface Cleaning”. International Journal of Advanced Computer Science and Applications (IJACSA) 17.5 (2026). http://dx.doi.org/10.14569/IJACSA.2026.0170583

@article{NABOU2026,
title = {Optimizing Whiteboard Digitization with Clarix: An Automated Vision-Based System for Real-Time Text Extraction and Surface Cleaning},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2026.0170583},
url = {http://dx.doi.org/10.14569/IJACSA.2026.0170583},
year = {2026},
publisher = {The Science and Information Organization},
volume = {17},
number = {5},
author = {Abdellah NABOU and Ameksa Mohammed and Ezzahoud Hajar and Bazgour Yassine and Abouhane Zahra}
}