In this paper,a software/hardware High-level Synthesis(HLS)design is proposed to compute the Adaptive Vector Median Filter(AVMF)in realtime.In fact,this filter is known by its excellent impulsive noise suppression and...In this paper,a software/hardware High-level Synthesis(HLS)design is proposed to compute the Adaptive Vector Median Filter(AVMF)in realtime.In fact,this filter is known by its excellent impulsive noise suppression and chromaticity conservation.The software(SW)study of this filter demonstrates that its implementation is too complex.The purpose of this work is to study the impact of using an HLS tool to design ideal floating-point and optimized fixed-point hardware(HW)architectures for the AVMF filter using square root function(ideal HW)and ROM memory(optimized HW),respectively,to select the best HLS architectures and to design an efficient HLS software/hardware(SW/HW)embedded AVMF design to achieve a trade-off between the processing time,power consumption and hardware cost.For that purpose,some approximations using ROM memory were proposed to perform the square root and develop a fixed-point AVMF algorithm.After that,the best solution generated for each HLS design was integrated in the SW/HW environment and evaluated under ZC702 FPGA platform.The experimental results showed a reduction of about 65%and 98%in both the power consumption and processing time for the ideal SW/HW implementation relative to the ideal SW implementation for an AVMF filter with the same image quality,respectively.Moreover,the power consumption and processing time of the optimized SW/HW are 70%and 97%less than the optimized SW implementation,respectively.In addition,the Look Up Table(LUTs)percentage,power consumption and processing time used by the optimized SW/HW design are improved by nearly 45%,18%and 61%compared the ideal SW/HW design,respectively,with slight decrease in the image quality.展开更多
The challenge faced by the visually impaired persons in their day-today lives is to interpret text from documents.In this context,to help these people,the objective of this work is to develop an efficient text recogni...The challenge faced by the visually impaired persons in their day-today lives is to interpret text from documents.In this context,to help these people,the objective of this work is to develop an efficient text recognition system that allows the isolation,the extraction,and the recognition of text in the case of documents having a textured background,a degraded aspect of colors,and of poor quality,and to synthesize it into speech.This system basically consists of three algorithms:a text localization and detection algorithm based on mathematical morphology method(MMM);a text extraction algorithm based on the gamma correction method(GCM);and an optical character recognition(OCR)algorithm for text recognition.A detailed complexity study of the different blocks of this text recognition system has been realized.Following this study,an acceleration of the GCM algorithm(AGCM)is proposed.The AGCM algorithm has reduced the complexity in the text recognition system by 70%and kept the same quality of text recognition as that of the original method.To assist visually impaired persons,a graphical interface of the entire text recognition chain has been developed,allowing the capture of images from a camera,rapid and intuitive visualization of the recognized text from this image,and text-to-speech synthesis.Our text recognition system provides an improvement of 6.8%for the recognition rate and 7.6%for the F-measure relative to GCM and AGCM algorithms.展开更多
基金The authors extend their appreciation to the Deanship of Scientific Research at Jouf University(Kingdom of Saudi Arabia)for funding this work through research Grant No.DSR2020-06-3663.
文摘In this paper,a software/hardware High-level Synthesis(HLS)design is proposed to compute the Adaptive Vector Median Filter(AVMF)in realtime.In fact,this filter is known by its excellent impulsive noise suppression and chromaticity conservation.The software(SW)study of this filter demonstrates that its implementation is too complex.The purpose of this work is to study the impact of using an HLS tool to design ideal floating-point and optimized fixed-point hardware(HW)architectures for the AVMF filter using square root function(ideal HW)and ROM memory(optimized HW),respectively,to select the best HLS architectures and to design an efficient HLS software/hardware(SW/HW)embedded AVMF design to achieve a trade-off between the processing time,power consumption and hardware cost.For that purpose,some approximations using ROM memory were proposed to perform the square root and develop a fixed-point AVMF algorithm.After that,the best solution generated for each HLS design was integrated in the SW/HW environment and evaluated under ZC702 FPGA platform.The experimental results showed a reduction of about 65%and 98%in both the power consumption and processing time for the ideal SW/HW implementation relative to the ideal SW implementation for an AVMF filter with the same image quality,respectively.Moreover,the power consumption and processing time of the optimized SW/HW are 70%and 97%less than the optimized SW implementation,respectively.In addition,the Look Up Table(LUTs)percentage,power consumption and processing time used by the optimized SW/HW design are improved by nearly 45%,18%and 61%compared the ideal SW/HW design,respectively,with slight decrease in the image quality.
基金This work was funded by the Deanship of Scientific Research at Jouf University under Grant Number(DSR2022-RG-0114).
文摘The challenge faced by the visually impaired persons in their day-today lives is to interpret text from documents.In this context,to help these people,the objective of this work is to develop an efficient text recognition system that allows the isolation,the extraction,and the recognition of text in the case of documents having a textured background,a degraded aspect of colors,and of poor quality,and to synthesize it into speech.This system basically consists of three algorithms:a text localization and detection algorithm based on mathematical morphology method(MMM);a text extraction algorithm based on the gamma correction method(GCM);and an optical character recognition(OCR)algorithm for text recognition.A detailed complexity study of the different blocks of this text recognition system has been realized.Following this study,an acceleration of the GCM algorithm(AGCM)is proposed.The AGCM algorithm has reduced the complexity in the text recognition system by 70%and kept the same quality of text recognition as that of the original method.To assist visually impaired persons,a graphical interface of the entire text recognition chain has been developed,allowing the capture of images from a camera,rapid and intuitive visualization of the recognized text from this image,and text-to-speech synthesis.Our text recognition system provides an improvement of 6.8%for the recognition rate and 7.6%for the F-measure relative to GCM and AGCM algorithms.
