Multilingual Handwritten OCR using CLIP and Tesseract
Abhishek Singh Sengar · International Journal for Research in Applied Science and Engineering Technology · 2025
Optical Character Recognition (OCR) of handwritten text is an extremely challenging problem, particularly in multilingual and low-resource environments. Conventional OCR engines like Tesseract work well for printed text but not for handwriting because of extreme variations in style, language, and noise. The breakthroughs in multimodal models, especially CLIP (Contrastive Language–Image Pretraining), provide new avenues agnostic knowledge This paper discusses the possibility of combining CLIP with Tesseract to improve multilingual handwritten OCR, covering current methods, limitations, and future research directions.