Character Recognition and Extraction using OpenCV and Pytesseract

Abstract—This paper introduces an optimized framework for real-time Optical Character Recognition (OCR) and video-to- text conversion using OpenCV and Tesseract, by implementing adaptive preprocessing techniques and efficient frame handling strategies, the system achieves high text detection accuracy while significantly reducing processing time. Additionally, a multi- threaded audio transcription process enhances performance for converting video content into text. The proposed approach is well- suited for applications requiring real-time text extraction from multimedia sources, such as automated document processing and video surveillance.. Index Terms—OCR, Pytesseract, Cv2

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Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-04-29
DOI
https://doi.org/10.55041/ijsrem46150
Primary Topic
Handwritten Text Recognition Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Character Recognition and Extraction using OpenCV and Pytesseract

K. T. V. Reddy
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Handwritten Text Recognition Techniques
article

Character Recognition and Extraction using OpenCV and Pytesseract

K. T. V. Reddy
article en

Abstract

Abstract—This paper introduces an optimized framework for real-time Optical Character Recognition (OCR) and video-to- text conversion using OpenCV and Tesseract, by implementing adaptive preprocessing techniques and efficient frame handling strategies, the system achieves high text detection accuracy while significantly reducing processing time. Additionally, a multi- threaded audio transcription process enhances performance for converting video content into text. The proposed approach is well- suited for applications requiring real-time text extraction from multimedia sources, such as automated document processing and video surveillance.. Index Terms—OCR, Pytesseract, Cv2

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(04)
Openalex Percentile: Top 93%
Handwritten Text Recognition Techniques
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