GLM-OCR vs. Tesseract: A Comparative Analysis of LLM-Based OCR

This article presents a fascinating comparison between GLM-OCR, a vision-based Large Language Model (LLM), and the traditional Tesseract OCR engine. The study meticulously analyzes their performance on book images, providing valuable insights into the strengths and potential challenges of LLM-based approaches in the field of Computer Vision and Natural Language Processing (NLP).

• •GLM-OCR, using an LLM, was compared to Tesseract for OCR of book images.
• •GLM-OCR produced more output files, including whole-page scans and cut-out portions.
• •A significant difference observed was the issue of repetitive output in GLM-OCR.