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Embedded System Based Raspberry Pi 4 for Text Detection and Recognition

Turki M. Alanazi*

Department of Electrical Engineering, College of Engineering, Jouf University, Sakaka, Saudi Arabia

* Corresponding Author: Turki M. Alanazi. Email: email

Intelligent Automation & Soft Computing 2023, 36(3), 3343-3354. https://doi.org/10.32604/iasc.2023.036411

Abstract

Detecting and recognizing text from natural scene images presents a challenge because the image quality depends on the conditions in which the image is captured, such as viewing angles, blurring, sensor noise, etc. However, in this paper, a prototype for text detection and recognition from natural scene images is proposed. This prototype is based on the Raspberry Pi 4 and the Universal Serial Bus (USB) camera and embedded our text detection and recognition model, which was developed using the Python language. Our model is based on the deep learning text detector model through the Efficient and Accurate Scene Text Detector (EAST) model for text localization and detection and the Tesseract-OCR, which is used as an Optical Character Recognition (OCR) engine for text recognition. Our prototype is controlled by the Virtual Network Computing (VNC) tool through a computer via a wireless connection. The experiment results show that the recognition rate for the captured image through the camera by our prototype can reach 99.75% with low computational complexity. Furthermore, our prototype is more performant than the Tesseract software in terms of the recognition rate. Besides, it provides the same performance in terms of the recognition rate with a huge decrease in the execution time by an average of 89% compared to the EasyOCR software on the Raspberry Pi 4 board.

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Cite This Article

APA Style
Alanazi, T.M. (2023). Embedded system based raspberry pi 4 for text detection and recognition. Intelligent Automation & Soft Computing, 36(3), 3343-3354. https://doi.org/10.32604/iasc.2023.036411
Vancouver Style
Alanazi TM. Embedded system based raspberry pi 4 for text detection and recognition. Intell Automat Soft Comput . 2023;36(3):3343-3354 https://doi.org/10.32604/iasc.2023.036411
IEEE Style
T.M. Alanazi, "Embedded System Based Raspberry Pi 4 for Text Detection and Recognition," Intell. Automat. Soft Comput. , vol. 36, no. 3, pp. 3343-3354. 2023. https://doi.org/10.32604/iasc.2023.036411



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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