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Article Dans Une Revue CMC-Computers, Materials & Continua Année : 2022

An Efficient HW/SW Design for Text Extraction from Complex Color Image

Résumé

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.
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Dates et versions

hal-03641627 , version 1 (14-04-2022)

Identifiants

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Mohamed Amin Ben Atitallah, Rostom Kachouri, Ahmed Ben Atitallah, Hassene Mnif. An Efficient HW/SW Design for Text Extraction from Complex Color Image. CMC-Computers, Materials & Continua, 2022, 71 (3), pp.5963-5977. ⟨10.32604/cmc.2022.024345⟩. ⟨hal-03641627⟩
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