International Journal on Science and Technology

E-ISSN: 2229-7677     Impact Factor: 9.88

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 16 Issue 2 April-June 2025 Submit your research before last 3 days of June to publish your research paper in the issue of April-June.

Text Extraction and Detection from Images using CRNN and Security Algorithm

Author(s) Yerramsetti Jagan Pavan Kumar, Cheepulla Santha Kumari, Pragada Bhagya Lakshmi, Gokanaboina Balakrishna, Podila Purna Chandra Rao
Country India
Abstract The rapid digitalization of text information calls for cost-effective and safe optical character recognition (OCR) methods. Herein, the current paper advocates an advanced text detection and text extraction scheme for images using a deep learning architecture incorporating Recurrent Neural Networks (RNN) along with cryptography based on AES. The model improves text recognition and detection accuracy with a hybrid Convolution Neural Network (CNN)-RNN model in conjunction with text localization methods like Efficient and Accurate Scene Text Detector (EAST) and Connectionist Text Proposal Network (CTPN). For maintaining data integrity and security, the extracted text is encrypted with AES, which offers a tamper-proof solution for safe document processing. Experimental evaluation on benchmark datasets (ICDAR 2013, SVT, IIIT 5K) and a self-created dataset of 5,000 images shows superior performance with an attained 5.2% Character Error Rate (CER) and 7.3% Word Error Rate (WER) much higher compared to standard OCR models like Tesseract. The suggested framework also attains a 91.6% F1-score in the ICDAR 2013 dataset and demonstrates strong adaptability for handwritten, printed, and scene text in different environments. Additionally, computational efficiency in the AES encryption mechanism provides little overhead, thereby making the system appropriate for real-time use. This work contributes to OCR technology by tackling both accuracy and security, providing a secure and scalable solution for industries needing automated text recognition, including finance, healthcare, and legal document processing.
Keywords Optical Character Recognition (OCR), Deep Learning, Recurrent Neural Networks (RNN), AES Encryption, Secure Text Extraction, Image Processing
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 16, Issue 2, April-June 2025
Published On 2025-04-01
Cite This Text Extraction and Detection from Images using CRNN and Security Algorithm - Yerramsetti Jagan Pavan Kumar, Cheepulla Santha Kumari, Pragada Bhagya Lakshmi, Gokanaboina Balakrishna, Podila Purna Chandra Rao - IJSAT Volume 16, Issue 2, April-June 2025.

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