• Shivam kumar
• amit kumar ram
• pragati
• jay kishan

Abstract— Optical Character Recognition (OCR) is a transformative technology that enables the automatic extraction of text from scanned documents and images, converting it into editable, searchable digital formats. This paper explores the evolution, underlying mechanisms, and current advancements in OCR systems. It examines core OCR processes, including image preprocessing, character segmentation, feature extraction, and classification, highlighting the roles of machine learning and deep learning algorithms in enhancing OCR accuracy and adaptability. Despite substantial improvements, challenges remain in recognizing text with complex backgrounds, low resolution, and handwritten or stylized fonts. The paper discusses various applications of OCR across industries such as healthcare, finance, transportation, and education, where it facilitates data accessibility and automation. Additionally, we address ethical considerations surrounding data privacy and security in OCR applications. Through this comprehensive review, we aim to outline current OCR capabilities, limitations, and future directions, emphasizing the need for hybrid approaches and artificial intelligence to further enhance OCR’s effectiveness in diverse real-world scenarios. OCR continues to hold great potential for streamlining workflows and fostering accessibility across digital ecosystems.

Keywords - Optical Character Recognition, OCR technology, text extraction, machine learning, deep learning, data accessibility, document digitization, handwritten text recognition, information security.

"OPTICAL CHARACTER RECOGNITION SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.a477-a484, November-2024, Available :http://www.jetir.org/papers/JETIR2411050.pdf

"OPTICAL CHARACTER RECOGNITION SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. ppa477-a484, November-2024, Available at : http://www.jetir.org/papers/JETIR2411050.pdf