An Efficient HW/SW Design for Text Extraction from Complex Color Image
- Mohamed Amin Ben Atitallah1,2,3,*, Rostom Kachouri2, Ahmed Ben Atitallah4, Hassene Mnif1
1 LETI (E.N.I.S.), University of Sfax, Sfax, Tunisia
2 Laboratory of informatics, Gaspard-Monge, A3SI, ESIEE Paris, CNRS, Gustave Eiffel University, France
3 National Engineering School of Gabes (ENIG), University of Gabes, Tunisia
4 Department of Electrical Engineering, Jouf University, Sakaka, Aljouf, Saudi Arabia
* Corresponding Author: Mohamed Amin Ben Atitallah. Email:
2 Laboratory of informatics, Gaspard-Monge, A3SI, ESIEE Paris, CNRS, Gustave Eiffel University, France
3 National Engineering School of Gabes (ENIG), University of Gabes, Tunisia
4 Department of Electrical Engineering, Jouf University, Sakaka, Aljouf, Saudi Arabia
* Corresponding Author: Mohamed Amin Ben Atitallah. Email:
Received 14 October 2021; Accepted 26 November 2021; Issue published 14 January 2022
Abstract
In the context of constructing an embedded system to help visually impaired people to interpret text, in this paper, an efficient High-level synthesis (HLS) Hardware/Software (HW/SW) design for text extraction using the Gamma Correction Method (GCM) is proposed. Indeed, the GCM is a common method used to extract text from a complex color image and video. The purpose of this work is to study the complexity of the GCM method on Xilinx ZCU102 FPGA board and to propose a HW implementation as Intellectual Property (IP) block of the critical blocks in this method using HLS flow with taking account the quality of the text extraction. This IP is integrated and connected to the ARM Cortex-A53 as coprocessor in HW/SW codesign context. The experimental results show that the HLS HW/SW implementation of the GCM method on ZCU102 FPGA board allows a reduction in processing time by about 89% compared to the SW implementation. This result is given for the same potency and strength of SW implementation for the text extraction.
Keywords
Text extraction; GCM; HW/SW codesign; FPGA; HLS flow
Cite This Article
Amin, M., Kachouri, R., Atitallah, A. B., Mnif, H. (2022). An Efficient HW/SW Design for Text Extraction from Complex Color Image. CMC-Computers, Materials & Continua, 71(3), 5963–5977.
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