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Journal articles on the topic 'Field-programmable gate array Medical image'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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1

Prakash, Marakumbi, and Bhairannawar Satish. "Efficient reconfigurable architecture to enhance medical image security." Efficient reconfigurable architecture to enhance medical image security 30, no. 3 (2023): 1516–24. https://doi.org/10.11591/ijeecs.v30.i3.pp1516-1524.

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Medical images are one of the most critical and sensitive types of data in information systems. For the secure storage and transfer of medical images, confidentiality is the most important aspect. This paper presents efficient embedding technique to enhance medical image security. The Gaussian filters are used as preprocessing to remove high frequency components and then applied to cumulative distribution function (CDF) 5/3 wavelet to obtain LL band features. Similarly, the LL band features of cover image are obtained. The alpha bending technique combines both the LL band features of cover and

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Ahmad, A., A. Amira, H. Rabah, and Y. Berviller. "Medical image denoising on field programmable gate array using finite Radon transform." IET Signal Processing 6, no. 9 (2012): 862–70. http://dx.doi.org/10.1049/iet-spr.2011.0392.

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Ch, Gangadhar, and Md Habibulla. "Lucas Algorithm for Medical Images Encryption and Transmission using Orthogonal Frequency Division Multiplexing for Medical Health Information Systems and its VLSI Realization." International Journal of Online and Biomedical Engineering (iJOE) 17, no. 06 (2021): 128. http://dx.doi.org/10.3991/ijoe.v17i06.23107.

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<p>Security of medical images is critical for transmission of medical images and relevant patient information through public health information systems networks. Image encryption is an important tool for protecting Medical images by converting them into unrecognisable formats for the transmission and receiption of medical images. This paper proposes an algorithm for medical image encryption using Lucas Algorithm, and a discrete wavelet transform based transmission and reception technique, which is known as orthogonal frequency division multiplexing(OFDM). This paper presents an implement

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Mo, Handong, Xinhong Zhou, and Chenglang L. "Design of a real-time image processing system based on FPGA." Advances in Engineering Innovation 9, no. 1 (2024): 63–67. http://dx.doi.org/10.54254/2977-3903/9/2024094.

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To enhance the real-time performance of image processing, effectively reduce video transmission bandwidth and storage space, and improve transmission efficiency, a real-time image processing system was designed using a Field Programmable Gate Array (FPGA). The system is mainly divided into image acquisition, image processing, and image display subsystems. Images are captured using a camera module and transmitted to the image processing module for processing, and finally displayed via an HDMI monitor. Measurements indicate that the system has strong real-time performance, low power consumption,

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Younis, Ahmed Khazal, Basma Mohammed Kamal Younis, and Mohammed Sabah Jarjees. "Hardware implementation of Sobel edge detection system for blood cells images-based field programmable gate array." Indonesian Journal of Electrical Engineering and Computer Science 26, no. 1 (2022): 86–95. https://doi.org/10.11591/ijeecs.v26.i1.pp86-95.

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The microscopic-blood image has been used to diagnose various diseases according to the morphological specifications of red and white blood cells. However, the manual analysis and procedures are not accurate due to the human error. Therefore, several studies conducted to find new techniques to perform this analysis using computer algorithms. The complexity of these algorithms led to thinking in simpler ways or to the hardware solutions. On the other hand, edge detection is a mathematical procedure that play an essential role in the field of medical image processing. It is considered as one of

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Baskaran, S., L. Mubark Ali, A. Anitharani, E. Annal Sheeba Rani, and N. Nandhagopal. "Pupil Detection System Using Intensity Labeling Algorithm in Field Programmable Gate Array." Journal of Computational and Theoretical Nanoscience 17, no. 12 (2020): 5364–67. http://dx.doi.org/10.1166/jctn.2020.9429.

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Pupil detection techniques are an essential diagnostic technique in medical applications. Pupil detection becomes more complex because of the dynamic movement of the pupil region and it’s size. Eye-tracking is either the method of assessing the point of focus (where one sees) or the orientation of an eye relative to the head. An instrument used to control eye positions and eye activity is the eye tracker. As an input tool for human-computer interaction, eye trackers are used in research on the visual system, in psychology, psycholinguistics, marketing, and product design. Eye detection is one

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Younis, Ahmed Khazal, Basma MohammedKamal Younis, and Mohammed Sabah Jarjees. "Hardware implementation of Sobel edge detection system for blood cells images-based field programmable gate array." Indonesian Journal of Electrical Engineering and Computer Science 26, no. 1 (2022): 86. http://dx.doi.org/10.11591/ijeecs.v26.i1.pp86-95.

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The microscopic-blood image has been used to diagnose various diseases according to the morphological specifications of red and white blood cells. <span lang="EN-US">However, the manual analysis and procedures are not accurate due to the human error. Therefore, several studies conducted to find new techniques to perform this analysis using computer algorithms. The complexity of these algorithms led to thinking in simpler ways or to the hardware solutions. On the other hand, edge detection is a mathematical procedure that play an essential role in the field of medical image processing. It

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Devasena, D., M. Jagadeeswari, and K. Srinivasan. "Development of Optimized Algorithm and Field Programmable Gate Array Implementation for Bio Medical Image Denoising for Health Informatics Applications." Journal of Medical Imaging and Health Informatics 11, no. 10 (2021): 2626–38. http://dx.doi.org/10.1166/jmihi.2021.3851.

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Denoising images is a most difficult task in applications for image processing. The image specifics are preserved and the additional sounds found in the images are removed. It is also a challenge to remove noise from medical and satellite images. It improves the diagnostic capacity of medical images and satellite images visual clarity. The noise in the images varies and its density varies depending on imaging techniques. The algorithms in the literature were suggested based on the noise density and the forms of noise. The aim of this paper is to eliminate the noise from ultrasound, magnetic re

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Marakumbi, Prakash, and Satish Bhairannawar. "Efficient reconfigurable architecture to enhance medical image security." Indonesian Journal of Electrical Engineering and Computer Science 30, no. 3 (2023): 1516. http://dx.doi.org/10.11591/ijeecs.v30.i3.pp1516-1524.

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Medical images are one of the most critical and sensitive types of data in information systems. For the secure storage and transfer of medical images, confidentiality is the most important aspect. This paper presents efficient embedding technique to enhance medical image security. The Gaussian filters are used as preprocessing to remove high frequency components and then applied to cumulative distribution function (CDF) 5/3 wavelet to obtain LL band features. Similarly, the LL band features of cover image are obtained. The alpha bending technique combines both the LL band features of cover and

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Mushtaq, Uzma, Osman Hasan, and Falah Awwad. "NoC-Based Implementation of Free Form Deformations in Medical Imaging Registration." Journal of Circuits, Systems and Computers 26, no. 04 (2016): 1750058. http://dx.doi.org/10.1142/s021812661750058x.

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These days, computer-based image registration techniques are increasingly being used in the area of medical imaging as they offer significant benefits for aligning different images together and for visualizing their combined images. However, these techniques require an enormous amount of computation time due to the high resolution and complex nature of the medical images. We propose to alleviate this problem by using a dedicated Network-on-Chip (NoC)-based hardware platform for image registration. This paper describes a novel technique for field-programmable gate array (FPGA) implementation of

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Dhouibi, Meriam, Ahmed Karim Ben Salem, Afef Saidi, and Slim Ben Saoud. "Acceleration of convolutional neural network based diabetic retinopathy diagnosis system on field programmable gate array." International Journal of Informatics and Communication Technology (IJ-ICT) 12, no. 3 (2023): 214. http://dx.doi.org/10.11591/ijict.v12i3.pp214-224.

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Diabetic retinopathy (DR) is one of the most common causes of blindness. The necessity for a robust and automated DR screening system for regular examination has long been recognized in order to identify DR at an early stage. In this paper, an embedded DR diagnosis system based on convolutional neural networks (CNNs) has been proposed to assess the proper stage of DR. We coupled the power of CNN with transfer learning to design our model based on state-of-the-art architecture. We preprocessed the input data, which is color fundus photography, to reduce undesirable noise in the image. After tra

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Meriam, Dhouibi, Karim Ben Salem Ahmed, Saidi Afef, and Ben Saoud Slim. "Acceleration of convolutional neural network based diabetic retinopathy diagnosis system on field programmable gate array." International Journal of Informatics and Communication Technology 12, no. 3 (2023): 214–24. https://doi.org/10.11591/ijict.v12i3.pp214-224.

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Diabetic retinopathy (DR) is one of the most common causes of blindness. The necessity for a robust and automated DR screening system for regular examination has long been recognized in order to identify DR at an early stage. In this paper, an embedded DR diagnosis system based on convolutional neural networks (CNNs) has been proposed to assess the proper stage of DR. We coupled the power of CNN with transfer learning to design our model based on state-of-the-art architecture. We preprocessed the input data, which is color fundus photography, to reduce undesirable noise in the image. After tra

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Grava, Cristian, Alexandru Gacsádi, and Ioan Buciu. "A Homogeneous Algorithm for Motion Estimation and Compensation by Using Cellular Neural Networks." International Journal of Computers Communications & Control 5, no. 5 (2010): 719. http://dx.doi.org/10.15837/ijccc.2010.5.2231.

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In this paper we present an original implementation of a homogeneous algorithm for motion estimation and compensation in image sequences, by using Cellular Neural Networks (CNN). The CNN has been proven their efficiency in real-time image processing, because they can be implemented on a CNN chip or they can be emulated on Field Programmable Gate Array (FPGA). The motion information is obtained by using a CNN implementation of the well-known Horn &amp; Schunck method. This information is further used in a CNN implementation of a motion-compensation method. Through our algorithm we obtain a

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Chavarria, Mario Andrés, Matthias Huser, Sebastien Blanc, et al. "X-ray imaging detector for radiological applications adapted to the context and requirements of low- and middle-income countries." Review of Scientific Instruments 93, no. 3 (2022): 034102. http://dx.doi.org/10.1063/5.0077985.

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This paper describes the development of a novel medical x-ray imaging system adapted to the needs and constraints of low- and middle-income countries. The developed system is based on an indirect conversion chain: a scintillator plate produces visible light when excited by the x rays, and then, a calibrated multi-camera architecture converts the visible light from the scintillator into a set of digital images. The partial images are then unwarped, enhanced, and stitched through parallel field programmable gate array processing units and specialized software. All the detector components were ca

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SG, Sreejeesh, and Sakthivel R. "An Efficient Parallel Architecture for Sub Band Processor in Broad Band MVDR Beamformer for Medical Ultrasound Applications." International Journal of Emerging Technology and Advanced Engineering 11, no. 6 (2021): 27–39. http://dx.doi.org/10.46338/ijetae0621_04.

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Minimum Variance Distortion less Response (MVDR) algorithm is the key adaptive beamforming algorithm in high resolution Medical Ultrasound Imaging systems. MVDR Beamformer is a frequency domain beamformer, and each frequency sub band need to be processed to generate covariance matrix and the same is computationally costly. Though many VLSI architectures have been proposed for MVDR Beamformer, currently no Complex Correlation matrix generation architecture for frequency sub band has been devised which supports real time implementation of broad band MVDR Beamformer for Medical Ultrasound Imaging

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Abo-Elftooh, Bassam A., Mohamed H. El-Mahlawy, and Mahmoud E. A. Gadallah. "Efficient Computerized-Tomography Reconstruction Using Low-Cost FPGA-DSP Chip." Electronics ETF 21, no. 1 (2017): 12. http://dx.doi.org/10.7251/els1721012a.

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In this paper, filtered back-projection algorithm is optimally implemented using low-cost Spartan 3A-DSP 3400 chip. The optimization enables parallel implementation. The combination of the pixel parallelism and projection parallelism is presented to significantly reduce the total reconstruction time to produce the image. The applied data is presented in fixed point format to achieve efficient implementation with maximum speed. The selection of data bus-width is optimized with very little error and good visual quality required for medical images. Before implementation, the computer tomography (

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Huda Ja’afar, Noor, and Afandi Ahmad. "Pipeline architectures of Three-dimensional daubechies wavelet transform using hybrid method." Indonesian Journal of Electrical Engineering and Computer Science 15, no. 1 (2019): 240. http://dx.doi.org/10.11591/ijeecs.v15.i1.pp240-246.

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<span>The application of three-dimensional (3-D) medical image compression systems uses several building blocks for its computationally intensive algorithms to perform matrix transformation operations. Complexity in addressing large medical volumes data has resulted in vast challenges from a hardware implementation perspective. This paper presents an approach towards very-large-scale-integration (VLSI) implementation of 3-D Daubechies wavelet transform for medical image compression. Discrete wavelet transform (DWT) algorithm is used to design the proposed architectures with pipelined dir

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Arasu, S. P. Valan, and S. Baulkani. "An Efficient FPGA Architecture with High-Performance 2D DWT Processor for Medical Imaging." Journal of Circuits, Systems and Computers 25, no. 09 (2016): 1650110. http://dx.doi.org/10.1142/s0218126616501103.

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Medical image fusion is the process of deriving vital information from multimodality medical images. Some important applications of image fusion are medical imaging, remote control sensing, personal computer vision and robotics. For medical diagnosis, computerized tomography (CT) gives the best information about denser tissue with a lesser amount of distortion and magnetic resonance image (MRI) gives the better information on soft tissue with little higher distortion. The main scheme is to combine CT and MRI images for getting most significant information. The need is to focus on less power co

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Yu, Jiaye. "The progress of image denoising based on FPGA." Highlights in Science, Engineering and Technology 131 (March 25, 2025): 29–34. https://doi.org/10.54097/2bpam373.

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With the increasing demand for high-quality images in applications such as intelligent driving and medical imaging, the removal of noise like Gaussian and salt-and-pepper noise has become a significant challenge. Traditional software-based denoising methods, while flexible, often fail to meet real-time performance and high throughput requirements, especially with the growing scale of image data. FPGA (Field-Programmable Gate Array) provides a promising alternative with its high parallelism and low power consumption, enabling efficient hardware-level image processing. This paper aims to FPGA-ba

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Chen, Yu, Dongxiang Lu, and Guy Courbebaisse. "A Parallel Image Registration Algorithm Based on a Lattice Boltzmann Model." Information 11, no. 1 (2019): 1. http://dx.doi.org/10.3390/info11010001.

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Image registration is a key pre-procedure for high level image processing. However, taking into consideration the complexity and accuracy of the algorithm, the image registration algorithm always has high time complexity. To speed up the registration algorithm, parallel computation is a relevant strategy. Parallelizing the algorithm by implementing Lattice Boltzmann method (LBM) seems a good candidate. In consequence, this paper proposes a novel parallel LBM based model (LB model) for image registration. The main idea of our method consists in simulating the convection diffusion equation throu

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Alanazi, Turki M., Kamel Berriri, Mohammed Albekairi, Ahmed Ben Atitallah, Anis Sahbani, and Khaled Kaaniche. "New Real-Time High-Density Impulsive Noise Removal Method Applied to Medical Images." Diagnostics 13, no. 10 (2023): 1709. http://dx.doi.org/10.3390/diagnostics13101709.

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This paper introduces a new method for real-time high-density impulsive noise elimination applied to medical images. A double process aimed at the enhancement of local data composed of Nested Filtering followed by a Morphological Operation (NFMO) is proposed. The major problem with heavily noisy images is the lack of color information around corrupted pixels. We show that the classic replacement techniques all come up against this problem, resulting in average restoration quality. We only focus on the corrupt pixel replacement phase. For the detection itself, we use the Modified Laplacian Vect

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Kumari, Cms Amrutha, and Syed Jahangir Badashah. "Image Edge Detection Using FPGA." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 10, no. 1 (2013): 1192–200. http://dx.doi.org/10.24297/ijct.v10i1.3323.

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Medical imaging often involves the injection of contrast agents and subsequent analysis of tissue enhancement patterns. X-ray angiograms are projections of 3D reality into 2D representations, there is a fair amount of self occlusion among the vessels, hence one cannot extract the vessels directly using the image intensities or gradients (edge) alone. Vessels extraction from angiogram images is useful for blood vessels measurement and computer visualizations of the coronary artery. This project describes the algorithm for automatic segmentation of coronary arteries in digital X-ray projections

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Dandekar, Omkar, William Plishker, Shuvra S. Bhattacharyya, and Raj Shekhar. "Multiobjective Optimization for Reconfigurable Implementation of Medical Image Registration." International Journal of Reconfigurable Computing 2008 (2008): 1–17. http://dx.doi.org/10.1155/2008/738174.

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In real-time signal processing, a single application often has multiple computationally intensive kernels that can benefit from acceleration using custom or reconfigurable hardware platforms, such as field-programmable gate arrays (FPGAs). For adaptive utilization of resources at run time, FPGAs with capabilities for dynamic reconfiguration are emerging. In this context, it is useful for designers to derive sets of efficient configurations that trade off application performance with fabric resources. Such sets can be maintained at run time so that the best available design tradeoff is used. Fi

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Shruti, V. H., and Patil Lakshmi. "REVIEW ON FPGA BASED HYBRID IMAGE FUSION MODEL FOR CT AND MRI IMAGES." Shodhasamhita : Journal of Fundamental & Comparative Research VIII, no. I (2023): 112–16. https://doi.org/10.5281/zenodo.8112654.

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In the medical field, digital image processing is used to diagnose patients' actions linked to various disorders. Because of significant advancements in medical diagnostics tools, assessment and reflection performance has substantially increased. In medical diagnostics, two significant techniques are computed tomography (CT) and magnetic resonance imaging (MRI). CT has less distortion and provides better information on denser tissues, whereas MRI has greater distortion and provides the best information on soft tissues. The combination of these clinical images has opened up a new intri

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Aydin, Seda Guzel, and Hasan Şakir Bilge. "FPGA Implementation of Image Registration Using Accelerated CNN." Sensors 23, no. 14 (2023): 6590. http://dx.doi.org/10.3390/s23146590.

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Background: Accurate and fast image registration (IR) is critical during surgical interventions where the ultrasound (US) modality is used for image-guided intervention. Convolutional neural network (CNN)-based IR methods have resulted in applications that respond faster than traditional iterative IR methods. However, general-purpose processors are unable to operate at the maximum speed possible for real-time CNN algorithms. Due to its reconfigurable structure and low power consumption, the field programmable gate array (FPGA) has gained prominence for accelerating the inference phase of CNN a

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Saood, Wesam Hujab, and Khamees Khalaf Hasan. "An Efficient Image Denoising Approach Using FPGA Type of PYNQ-Z2." Al-Kitab Journal for Pure Sciences 8, no. 02 (2024): 61–77. http://dx.doi.org/10.32441/kjps.08.02.p6.

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Image denoising techniques have become crucial for computer-assisted analysis due to the increasing number of digital images captured in unfavorable conditions. In various fields such as image recognition, medical imaging, robotics, and facial expression analysis, the presence of noise poses significant challenges for denoising algorithms. One of the key difficulties is distinguishing between edges, textures, and noise, all of which contain high-frequency components. Haar Wavelet Transform (HWT) has emerged as a highly effective technique for image denoising. The proposed study focuses on two

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Mendez, Tanya, Tejasvi Parupudi, Vishnumurthy Kedlaya K, and Subramanya G. Nayak. "Development of Power-Delay Product Optimized ASIC-Based Computational Unit for Medical Image Compression." Technologies 12, no. 8 (2024): 121. http://dx.doi.org/10.3390/technologies12080121.

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The proliferation of battery-operated end-user electronic devices due to technological advancements, especially in medical image processing applications, demands low power consumption, high-speed operation, and efficient coding. The design of these devices is centered on the Application-Specific Integrated Circuits (ASIC), General Purpose Processors (GPP), and Field Programmable Gate Array (FPGA) frameworks. The need for low-power functional blocks arises from the growing demand for high-performance computational units that are part of high-speed processors operating at high clock frequencies.

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Chervyakov, Nikolay, Pavel Lyakhov, and Nikolay Nagornov. "Analysis of the Quantization Noise in Discrete Wavelet Transform Filters for 3D Medical Imaging." Applied Sciences 10, no. 4 (2020): 1223. http://dx.doi.org/10.3390/app10041223.

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Denoising and compression of 2D and 3D images are important problems in modern medical imaging systems. Discrete wavelet transform (DWT) is used to solve them in practice. We analyze the quantization noise effect in coefficients of DWT filters for 3D medical imaging in this paper. The method for wavelet filters coefficients quantizing is proposed, which allows minimizing resources in hardware implementation by simplifying rounding operations. We develop the method for estimating the maximum error of 3D grayscale and color images DWT with various bits per color (BPC). The dependence of the peak

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Ghani, Arfan, Rawad Hodeify, Chan H. See, Simeon Keates, Dah-Jye Lee, and Ahmed Bouridane. "Computer Vision-Based Kidney’s (HK-2) Damaged Cells Classification with Reconfigurable Hardware Accelerator (FPGA)." Electronics 11, no. 24 (2022): 4234. http://dx.doi.org/10.3390/electronics11244234.

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In medical and health sciences, the detection of cell injury plays an important role in diagnosis, personal treatment and disease prevention. Despite recent advancements in tools and methods for image classification, it is challenging to classify cell images with higher precision and accuracy. Cell classification based on computer vision offers significant benefits in biomedicine and healthcare. There have been studies reported where cell classification techniques have been complemented by Artificial Intelligence-based classifiers such as Convolutional Neural Networks. These classifiers suffer

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Ramesh Solanki. "Hardware Acceleration of Image Processing Algorithms Using Vedic Multiplication in VLSI." Journal of Information Systems Engineering and Management 10, no. 26s (2025): 941–54. https://doi.org/10.52783/jisem.v10i26s.4310.

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The processing speed of the image processing operations is very high, and so efficient computation schemes are needed for high-speed computation with low power consumption. It is the common case with the majority of Very Large Scale Integration (VLSI) multiplication techniques that there is latency, power, and complexity involved with them. The work here discusses the implementation of Vedic Multiplication, an effective and high-speed arithmetic scheme, for accelerating image processing algorithms in VLSI circuits. The work comprises the integration of multipliers of Vedic mathematics into the

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Nagornov, N. N. "Defining of the Minimum Wavelet Filter Coefficients Bit-Width for 3D Medical Imaging." INFORMACIONNYE TEHNOLOGII 27, no. 8 (2021): 425–34. http://dx.doi.org/10.17587/it.27.425-434.

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Medical imaging uses a variety of modalities to provide visual information about a patient. Various methods are used to process this data. Many of them are based on discrete wavelet transform (DWT). Its use will allow effective denoising and compression of 2D and 3D images. This paper proposes a new approach to linear time-invariant wavelet filtering using quantized filter coefficients when using which the computational errors have different signs and allow to partially compensate each other as a result of which the processed image is of high quality. The analysis of the quantization noise of

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Kumari, Puja, and Dr Anita Kumari. "A Survey On Image Registration Techniques Using FFT." IOSR Journal of Mathematics 20, no. 5 (2024): 44–49. http://dx.doi.org/10.9790/0661-2005014449.

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Image Registration is the process of straightening two or more images of the same scene with testimonial to a particular image. The images are captured from various sensors at different times and at multiple viewpoints. Thus, to get a better picture of any change of a scene/object over a considerable period of time image registration is important. Image registration finds application in medical sciences, remote sensing and in computer vision. This paper presents a detailed review of several approaches which are classified accordingly along with their contributions and drawbacks. The main steps

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B, Devanathan, Selvaraju P, Thulasimani T, and Vishal Ratansing Patil. "FPGA-BASED HARDWARE ACCELERATION OF MACHINE LEARNING ALGORITHM FOR REAL-TIME IMAGE PROCESSING." ICTACT Journal on Microelectronics 9, no. 3 (2023): 1613–19. https://doi.org/10.21917/ijme.2023.0280.

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In real-time image processing, the demand for efficient solutions has surged with the proliferation of applications spanning from autonomous vehicles to medical diagnostics. This study addresses the imperative need for accelerated machine learning algorithms to enhance the processing speed of image-related tasks. The research focuses on leveraging Field-Programmable Gate Arrays (FPGAs) to implement hardware acceleration, exploiting their parallel computing capabilities. The advent of machine learning in image processing has revolutionized various industries, yet real-time applications encounte

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Orthy, Mumtahina, Sheikh Md Rabiul Islam, Faijah Rashid, and Md Asif Hasan. "Implementation of Image Enhancement and Edge Detection Algorithm on Diabetic Retinopathy (DR) Image Using FPGA." IET Circuits, Devices & Systems 2023 (December 11, 2023): 1–12. http://dx.doi.org/10.1049/2023/8820773.

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Diabetic retinopathy (DR) is an ocular ailment that may lead to loss of vision and eventual blindness among individuals diagnosed with diabetes. The blood vessels of the retina, a layer of light-sensitive tissue located at the posterior aspect of the ocular globe, are adversely impacted. The identification of DR entails the utilization of retinal fundus images. The detection of any form of abnormality in the eye through raw fundus images poses a significant challenge for medical practitioners. Hence, it is imperative to engage in the processing of fundus images. This paper delineates several i

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Rybalkin, Vladimir, Jonas Ney, Menbere Kina Tekleyohannes, and Norbert Wehn. "When Massive GPU Parallelism Ain’t Enough: A Novel Hardware Architecture of 2D-LSTM Neural Network." ACM Transactions on Reconfigurable Technology and Systems 15, no. 1 (2022): 1–35. http://dx.doi.org/10.1145/3469661.

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Multidimensional Long Short-Term Memory (MD-LSTM) neural network is an extension of one-dimensional LSTM for data with more than one dimension. MD-LSTM achieves state-of-the-art results in various applications, including handwritten text recognition, medical imaging, and many more. However, its implementation suffers from the inherently sequential execution that tremendously slows down both training and inference compared to other neural networks. The main goal of the current research is to provide acceleration for inference of MD-LSTM. We advocate that Field-Programmable Gate Array (FPGA) is

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Liao, Yu, Tian, Li, and Li. "A Quantized CNN-Based Microfluidic Lensless-Sensing Mobile Blood-Acquisition and Analysis System." Sensors 19, no. 23 (2019): 5103. http://dx.doi.org/10.3390/s19235103.

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This paper proposes a microfluidic lensless-sensing mobile blood-acquisition and analysis system. For a better tradeoff between accuracy and hardware cost, an integer-only quantization algorithm is proposed. Compared with floating-point inference, the proposed quantization algorithm makes a tradeoff that enables miniaturization while maintaining high accuracy. The quantization algorithm allows the convolutional neural network (CNN) inference to be carried out using integer arithmetic and facilitates hardware implementation with area and power savings. A dual configuration register group struct

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LI, XIAOYING, and ENHUA WU. "RELIEF TEXTURE MAPPING ON FIELD PROGRAMMABLE GATE ARRAY." International Journal of Image and Graphics 06, no. 04 (2006): 641–55. http://dx.doi.org/10.1142/s021946780600246x.

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Relief texture mapping is an image-based rendering technique which can successfully support the representation of 3D surface details and view motion parallax. It has the potential to significantly increase visual realism of rendered geometry while keeping system load constant. In this paper, FPGA (Field Programmable Gate Array) chip technology is applied to this three-dimensional image warping method. A relief texture mapping system has been implemented on a reprogrammable and reconfigurable FPGA board. The algorithm is optimized for the specific architecture and the framework is customized fo

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Lyu, Congyi, Haoyao Chen, Xin Jiang, Peng Li, and Yunhui Liu. "Real-time object tracking system based on field-programmable gate array and convolution neural network." International Journal of Advanced Robotic Systems 14, no. 1 (2016): 172988141668270. http://dx.doi.org/10.1177/1729881416682705.

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Vision-based object tracking has lots of applications in robotics, like surveillance, navigation, motion capturing, and so on. However, the existing object tracking systems still suffer from the challenging problem of high computation consumption in the image processing algorithms. The problem can prevent current systems from being used in many robotic applications which have limitations of payload and power, for example, micro air vehicles. In these applications, the central processing unit- or graphics processing unit-based computers are not good choices due to the high weight and power cons

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Ruiz-Rosero, Juan, Gustavo Ramirez-Gonzalez, and Rahul Khanna. "Field Programmable Gate Array Applications—A Scientometric Review." Computation 7, no. 4 (2019): 63. http://dx.doi.org/10.3390/computation7040063.

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Field Programmable Gate Array (FPGA) is a general purpose programmable logic device that can be configured by a customer after manufacturing to perform from a simple logic gate operations to complex systems on chip or even artificial intelligence systems. Scientific publications related to FPGA started in 1992 and, up to now, we found more than 70,000 documents in the two leading scientific databases (Scopus and Clarivative Web of Science). These publications show the vast range of applications based on FPGAs, from the new mechanism that enables the magnetic suspension system for the kilogram

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Xu, Guo Sheng. "Design of Data Acquisition System Based on FPGA." Advanced Materials Research 403-408 (November 2011): 1592–95. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.1592.

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A new kind of data acquisition system is introduced in this paper, in which the multi-channel synchronized real-time data acquisition under the coordinate control of field-programmable gate array(FPGA) is realized. The design uses field programmable gate arrays(FPGA) for the data processing and logic control. For high speed CCD image data processing, the paper adopts regional parallel processing based on FPGA. The FPGA inner block RAM is used to build high speed image data buffer is put into operation to achieve high speed image data integration and real-time processing. The proposed data acqu

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Li, Yiming. "Review on FPGA-based accelerators in convolutional neural network." Applied and Computational Engineering 4, no. 1 (2023): 666–72. http://dx.doi.org/10.54254/2755-2721/4/2023375.

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In current research, an important means to realize artificial intelligence is artificial neural network. Many tedious problemscan be solved by artificial neural network, such as image classification, speech recognition, natural language processing. Among neural networks, although convolutional neural network has significantly better performance in the field of image recognition, it requires many parameters and a large amount of computation, and the number of network layers is gradually increasing with the progress of the algorithm, which leads to model sizes are getting larger and more difficu

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Mohan, Rama. "Field Programmable Gate Array for Data Processing in Medical Systems." IOSR Journal of Electronics and Communication Engineering 7, no. 6 (2013): 58–62. http://dx.doi.org/10.9790/2834-0765862.

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Hong, Taeyang, Yongshin Kang, and Jaeyong Chung. "InSight: An FPGA-Based Neuromorphic Computing System for Deep Neural Networks." Journal of Low Power Electronics and Applications 10, no. 4 (2020): 36. http://dx.doi.org/10.3390/jlpea10040036.

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Deep neural networks have demonstrated impressive results in various cognitive tasks such as object detection and image classification. This paper describes a neuromorphic computing system that is designed from the ground up for energy-efficient evaluation of deep neural networks. The computing system consists of a non-conventional compiler, a neuromorphic hardware architecture, and a space-efficient microarchitecture that leverages existing integrated circuit design methodologies. The compiler takes a trained, feedforward network as input, compresses the weights linearly, and generates a time

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Duong, Huu Ai, Dat Vuong Cong, Ty Luong Khanh, and Truong Le Viet. "Field programmable gate array implementation of edge detection system based on an improved sobel edge detector." Indonesian Journal of Electrical Engineering and Computer Science 32, no. 3 (2023): 1378–83. https://doi.org/10.11591/ijeecs.v32.i3.pp1378-1383.

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Field programmable gate array (FPGA) is an integrated circuit consisting of internal hardware blocks with programmable link connections for users to customize operations for a particular application. Link connections can be easily reprogrammed, allowing the FPGA to adapt to changes to the design or even support a new application throughout the department's uptime. One of the important tasks in image processing is image edge detection image, with computer aided, image recognition is concerned with the recognition and classification of objects in an image, so edge detection is an important tool.

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Heo, Jinmoo, Seongjoo Lee, and Yunho Jung. "Field-Programmable Gate Array Implementation of Backprojection Algorithm for Circular Synthetic Aperture Radar." Electronics 14, no. 8 (2025): 1544. https://doi.org/10.3390/electronics14081544.

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This paper presents a backprojection algorithm (BPA) accelerator implemented on a field-programmable gate array (FPGA) for circular synthetic aperture radar (SAR) systems. Although the BPA offers superior image quality, it requires significantly more computation and is memory intensive, necessitating hardware optimization. In particular, the BPA accumulates image data, leading to high memory requirements that must be reduced for embedded system implementation. To address this issue, we optimized the floating-point (FP) bit width, focusing on the output data that form the image, rather than onl

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Huu Ai, Duong, Cong Dat Vuong, Khanh Ty Luong, and Viet Truong Le. "Field programmable gate array implementation of edge detection system based on an improved sobel edge detector." Indonesian Journal of Electrical Engineering and Computer Science 32, no. 3 (2023): 1378. http://dx.doi.org/10.11591/ijeecs.v32.i3.pp1378-1383.

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<p>Field programmable gate array (FPGA) is an integrated circuit consisting of internal hardware blocks with programmable link connections for users to customize operations for a particular application. Link connections can be easily reprogrammed, allowing the FPGA to adapt to changes to the design or even support a new application throughout the department's uptime. One of the important tasks in image processing is image edge detection image, with computer aided, image recognition is concerned with the recognition and classification of objects in an image, so edge detection is an import

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Sotohebo, Takashi, Minoru Watanabe, and Funtinori Kobayashi. "An FPGA Implementation of Finite Physical Quantity Neural Network." Journal of Robotics and Mechatronics 15, no. 2 (2003): 136–42. http://dx.doi.org/10.20965/jrm.2003.p0136.

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We propose installing a finite physical quantity neural network model on a high-density field programmable gate array (FPGA) at high speed by reducing multipliers. We could thereby downsize circuits without loss of precision. We evaluated its installation and experimental results for image recognition.

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Xu, Yang, Ping Li, Jian Jun Yuan, and Min Xiang. "The Research of Real-Time Image Acquisition and Sobel Edge Detection with FPGA." Key Engineering Materials 467-469 (February 2011): 703–8. http://dx.doi.org/10.4028/www.scientific.net/kem.467-469.703.

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As the real-time image acquiring and processing need to be dealt with high speed, a image acquisition and preprocessing system is discussed in this paper. It is built on FPGA( field programmable gate array ) with pipelined and parallel technology. The configurable macro function modules provided by Altera company achieve the Sobel edge detection algorithm. The real-time display the image after edge detection works properly and The new design method shorten the development cycle.

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Šušteršič, Tijana, and Aleksandar Peulić. "Implementation of Face Recognition Algorithm on Field Programmable Gate Array (FPGA)." Journal of Circuits, Systems and Computers 28, no. 08 (2019): 1950129. http://dx.doi.org/10.1142/s0218126619501299.

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The aim of this study is to implement an algorithm for face recognition, based on fast fourier transform (FFT), on the field programmable gate array (FPGA) chip. Implemented program included the initialization process of two single-IP-core ROM blocks, each with an image of a human face, which are sent to the real components of two-channel IP CoreFFT block. The result of classification could be displayed in the form of either a word “yes” or “no” on the seven-segment display or the information about the reference to the folder with the found match face. Due to the lack of memory on the chip, th

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Hoang, T. Tran, LT. Tran Dong, N. Pham Quang, et al. "Field programmable gate array based moving object tracking system for robot navigation." Bulletin of Electrical Engineering and Informatics 12, no. 2 (2023): 771~781. https://doi.org/10.11591/eei.v12i2.4538.

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This paper proposes a method in which an object tracking robot system is implemented on field programmable gate arrays (FPGAs). The OV7670 camera provides real-time object pictures to the system. To improve picture quality, images are put via the median filter phase. The item is distinguished from the backdrop based on color (red), after which it is subjected to a mathematical morphological approach of filtering to eliminate noise. To send the robot control signals, the object's (new) coordinates are found. In this method, the median filter, color separation, hardware IP cores, and morphol

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