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Recent Advances in Science and Engineering Technology (ICRASET), International Conference on

作者： N Rajesh I G Naveen N Shankari Parth Sheetal Kumthekar Sufiyan Ahmed Khan Rayyan Mohammed Department of ECE Nite Meenakshi Institute of Technology Bengaluru India NMAM Institute of Technology Nitte (Deemed to be University) Nitte Karnataka India

ISBN: (数字)9798350388602

ISBN: (纸本)9798350388619

Hyperspectral image processing plays a crucial role in various applications, including remote sensing and agricultural monitoring, yet it poses significant computational challenges due to the high dimensionality and intricate data structures involved. Traditional software-based methods often suffer from high processing time and latency, limiting their effectiveness in real-time applications. To address these challenges, we propose a hardware accelerator implemented on the Genesys 2 Kintex-7 FPGA Development Board, designed specifically for hyperspectral image enhancement. This FPGA-based solution employs parallel processing and optimized algorithms, including interpolation and super-resolution techniques, to significantly improve processing efficiency. We evaluate the performance of our proposed method using the Indian Pines dataset, a standard benchmark for hyperspectral imaging. Experimental results demonstrate that our FPGA implementation achieves a processing time of 50 ms, significantly faster than CPU and GPU solutions, while also reducing power consumption and improving energy efficiency. These findings underscore the potential of FPGA technology for enhancing hyperspectral image processing in resource-constrained environments.

关键词： Power demand Superresolution Graphics processing units parallel processing Real-time systems Field programmable gate arrays image enhancement Standards Hardware acceleration Hyperspectral imaging

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MatPIM: Accelerating Matrix Operations with Memristive Stateful Logic

MatPIM: Accelerating Matrix Operations with Memristive State...

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： Leitersdorf, Orian Ronen, Ronny Kvatinsky, Shahar Technion Israel Inst Technol Viterbi Fac Elect & Comp Engn Haifa Israel

ISBN: (纸本)9781665484855

The emerging memristive Memory processing Unit (mMPU) overcomes the memory wall through memristive devices that unite storage and logic for real processing-in-memory (PIM) systems. At the core of the mMPU is stateful logic, which is accelerated with memristive partitions to enable logic with massive inherent parallelism within crossbar arrays. This paper vastly accelerates the fundamental operations of matrix-vector multiplication and convolution in the mMPU, with either fullprecision or binary elements. These proposed algorithms establish an efficient foundation for large-scale mMPU applications such as neural-networks, image processing, and numerical methods. We overcome the inherent asymmetry limitation in the previous in-memory full-precision matrix-vector multiplication solutions by utilizing techniques from block matrix multiplication and reduction. We present the first fast in-memory binary matrixvector multiplication algorithm by utilizing memristive partitions with a tree-based popcount reduction ( 39x faster than previous work). For convolution, we present a novel in-memory inputparallel concept which we utilize for a full-precision algorithm that overcomes the asymmetry limitation in convolution, while also improving latency (2x faster than previous work), and the first fast binary algorithm (12x faster than previous work).

关键词： Memristor processing-in-memory parallel algorithms matrix multiplication convolution

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A pre-processing technique to decrease inspection time in glass tube production lines

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IET image processing 2021年第10期15卷 2179-2191页

作者： De Vitis, Gabriele Antonio Foglia, Pierfrancesco Prete, Cosimo Antonio Univ Pisa Dipartimento Ingn Informaz Via Diotisalvi 2 I-56100 Pisa Italy

In case of glass tube for pharmaceutical applications, high-quality defect detection is made via inspection systems based on computer vision. The processing must guarantee real-time inspection and meet increasing rate and quality requirements. Defect detection in glass tubes is complicated by aspects that hamper the efficiency of state-of-the-art techniques. This paper presents a pre-processing algorithm which excludes portions of the image where defects are surely absent. The approach decreases the time for defect detection and classification phases (any detection algorithm can be applied), as they are applied only in high-probability candidate sub-image. We derive a methodology to get robust values of algorithm's parameters during production. The algorithm relies on detrended standard deviation and double threshold hysteresis, which solve issues related to the misalignment between illuminator and acquisition camera, and enable a robust detection despite rotation, vibration, and irregularities of tubes. We consider Canny, MAGDDA, and Niblack algorithms. The solution keeps the detection quality of such algorithms and reaches a 4.69x throughput gain. It represents a methodology to obtain defect detection in time-constrained environments through a software-only approach, and can be exploited in parallel/accelerated solutions and in contexts where a linear camera is utilized on both flat and uneven surfaces.

关键词： robust detection detection algorithm time constrained environments probability quality requirements high probability candidate subimage automatic optical inspection preprocessing technique image sensors Niblack algorithms glass products inspection systems production engineering computing high quality defect detection preprocessing algorithm computer vision inspection time glass tube production lines image coding detection quality quality control real-time inspection

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Development and Characterization of a Hyperspectral LCTF-based Colposcopic System

Development and Characterization of a Hyperspectral LCTF-bas...

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Conference on Liquid Crystals Optics and Photonic Devices

作者： Vega, Carlos Marquez-Suarez, Nerea Leon, Raquel Castro-Femandez, Maria Socorro-Marrero, Guillermo, V Fabelo, Himar Rial-Ferrario, Jorge Callico, Gustavo M. Univ Las Palmas de Gran Canaria ULPGC Inst Appl Microelect IUMA Las Palmas Gran Canaria Spain Fdn Inst Invest Sanitaria Canarias FIISC Las Palmas Gran Canaria Spain OPTOMIC Espana SA Madrid Spain

ISBN: (纸本)9781510673519;9781510673502

The early detection of precancerous cervical lesions is essential to improve patient treatment and prognosis. Hyperspectral (HS) imaging (HSI) has demonstrated a high potential to become a new non-invasive and label-free imaging technique in the medical field for performing quick diagnosis of different diseases. This study presents the research and development process to integrate and characterize a KURIOS-xE2 filter (Thorlabs, Inc., NJ, USA), based in a liquid crystal tunable filter (LCTF) technology, into an existing colposcope (C5, OPTOMIC, Spain). The main goal was to capture spectral information in the near infrared range (650-1100 nm) by using a monochrome camera and acquiring 90 spectral wavelengths with a spectral resolution of 5 nm. Two different integration strategies were studied: i) filtering the emitted light by the sensor and ii) filtering the received light by the sensor, evaluating their respective benefits and limitations. Furthermore, a custom software was developed for HS image acquisition, integrating a variable acquisition time per wavelength, which allows improving the signal-to-noise ratio at wavelengths where the system presents lower quantum efficiency. The proposed system simplifies the adaptation of existing optical systems to HSI technology, improving the signal-to-noise ratio in the studied spectral range respect to other approaches. The results were compared against a previous custom implementation based on a Snapscan camera (IMEC, Belgium), covering the visual and near infrared and highlighting the advantages and limitations of both technologies for the development of a HS colposcope system targeting early detection of precancerous cervical lesions during routine clinical practice.

关键词： Hyperspectral imaging liquid crystal tunable filter cervical cancer image processing medical imaging medical instrumentation colposcopy

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Advancements in Structural Health Monitoring Using Combined Computer-Vision and Unmanned Aerial Vehicles Approaches 10th

Advancements in Structural Health Monitoring Using Combined ...

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10th European Workshop on Structural Health Monitoring (EWSHM)

作者： Sabato, Alessandro Niezrecki, Christopher Dabetwar, Shweta Kulkarni, Nitin Nagesh Bottalico, Fabio Nieduzak, Tymon Univ Massachusetts Lowell Dept Mech Engn Lowell MA 01852 USA

ISBN: (纸本)9783031072581;9783031072574

Aerospace, civil, energy, and mechanical engineering structures continue to be used despite reaching their design lifetime. Developing sensing and data analytics to assess the structural condition of the targeted systems is crucial. Traditional contact-based techniques may produce inconsistent results and are labor-intensive to be considered a valid alternative for monitoring large-scale structures such as bridges, large buildings, and wind turbines. Advancements in image-processing algorithms made techniques such as three-dimensional digital image correlation (3D-DIC), infrared thermography (IRT), motion magnification (MM), and structure from motion (SfM) appealing tools for structural health monitoring and non-destructive testing. Besides, as those techniques are implemented within unmanned aerial vehicles (UAVs), the measurement process is expedited while reducing interference with the targeted structure. This paper summarizes the research experience performed at the University of Massachusetts Lowell. The results of these activities show that the combination of autonomous flight with 3D-DIC, IRT, and SfM can provide precious insights into the structural conditions of the inspected systems while reducing downtime and costs. The study includes future research directions to make those approaches suitable for real-world applications.

关键词： Computer vision Digital image correlation Infrared imaging Motion magnification Optical techniques Structure from motion Unmanned aerial vehicles

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Compensation for Patient Movements in CBCT imaging for Dental applications 22nd

Compensation for Patient Movements in CBCT Imaging for Denta...

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22nd International Conference on image Analysis and processing (ICIAP)

作者： Ali, Abdul Salam Rasmi Asraf Sarti, Cristina Landi, Claudio Univ Udine Dept Engn & Architecture Udine Italy See Through Srl Brusaporto Italy

ISBN: (纸本)9783031431524;9783031431531

Cone Beam Computed Tomography (CBCT) is a popular imaging technique used in dentistry for diagnosis and treatment planning. However, patient movement during the scanning process can lead to image artifacts that can affect the accuracy of diagnosis and treatment planning. To address this issue, manufacturers have added mechanical fixations to CBCT systems to reduce patient motion, but these fixations are not completely rigid and still allow for some movement. Researchers have developed motion compensation algorithms to reduce the impact of motion artifacts on CBCT images. Nevertheless, these algorithms can be time-consuming and only partially address the problem. This paper proposes a new approach to motion compensation in CBCT imaging to overcome these limitations. Unlike traditional methods which use iterative approaches that require multiple reconstructions in the compensation stage, this new method uses a single initial reconstruction computed with the Feldkamp-Davis-Kress (FDK) algorithm. The reconstructed volume is regularized before the motion compensation step. Motion compensation is achieved by optimizing the motion parameters using a regularized 3D-2D image registration. The results show that the proposed non-iterative motion compensation approach effectively reduces motion-induced artifacts in the final reconstruction.

关键词： Dental CBCT motion compensation realistic motion simulation non-iterative method

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System-level design for DPCM image Compression with SoC-FPGA Accelerator

System-level design for DPCM Image Compression with SoC-FPGA...

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Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： Amin Safaei Samira Sabeti Morteza Masoudian Department of Computer Science Lakehead University Thunder Bay ON Canada

ISBN: (数字)9798350371628

ISBN: (纸本)9798350371635

The implementation of data compression in embedded platforms and portable systems is growing rapidly due to the demands for image and video processing in daily human life. Among the data compression applications, medical imaging, such as Computed Tomography (CT), and Light Detection And Ranging (LiDAR) have become active research areas, especially when data transmissions must be performed over a communication *** of the complexity of data compression algorithms and the high resolution of input streams, current embedded platforms may not be able to fully exploit data compression algorithms. To address this restriction, recent approaches utilize hardware accelerators to speed up the computation. Among available hardware accelerators, system-on-a-chip field-programmable gate arrays (SoC-FPGAs) have emerged as an important architecture approach in terms of achieving satisfactory computational performances. This study presents a hardware accelerator for the computation of a differential pulse code modulation (DPCM) algorithm implemented and synthesized on a Zynq SoC-FPGA and achieving an acceleration factor of 88x.

关键词： image coding Laser radar Computed tomography Data compression Computer architecture parallel processing Pulse modulation

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Optical processing for phased-array and beamspace mapping 15

Optical processing for phased-array and beamspace mapping

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Conference on Terahertz, RF, Millimeter, and Submillimeter-Wave Technology and applications xV

作者： Murakowski, Janusz Schneider, Garrett Prather, Dennis Univ Delaware Dept Elect & Comp Engn 140 Evans Hall Newark DE 19716 USA

ISBN: (数字)9781510648722

ISBN: (纸本)9781510648722;9781510648715

In imaging systems, a lens performs spatial Fourier transformation of the incoming waves, thereby mapping each plane wave into a point, or, equivalently, the lens focuses each set of parallel rays to a corresponding spot at the sensor array. Accordingly, two-dimensional (2D) vision requires a conventional 2D lens. This has been the common assumption since the dawn of free-space optics as a discipline. In this presentation. we demonstrate 2D image formation using a 1D lens. Such imaging is obtained in the context of RF phased arrays where image forming means beam forming of multiple beams simultaneously for receiving (transmitting) independent radio waves from (to) many different directions at the same time. The method is based on spatially coherent electro-optic up-conversion of the incoming radio signals to the optical domain and it exploits the arrangement of antennas in a regular array to map between different imaging topologies. Space-division multiple access (SDMA) enabled by this imaging modality is instrumental to ushering the age of virtually unlimited information bandwidth in wireless communication. The approach overcomes topological constraints of imaging systems in general. and of phased arrays in particular. We explain the principles of method and present experimental results illustrating its viability in a practical setting.

关键词： AB mapping phased array RF photonics imaging receiver imaging radiometer topological flexibility

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Design and Verification of an FPGA-Based MRI image Cluster processing

Design and Verification of an FPGA-Based MRI Image Cluster P...

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IEEE Southeastcon

作者： Abhiram Reddy Duvvuru Kumar Sai Reddy Guntaka Shrikant Jadhav Dept. Electrical Engineering San Jose State University San Jose USA Dept. Computer Engineering California State University Northridge Northridge USA

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

The FPGA-based MRI Cluster image processing System is designed to overcome the limitations of traditional MRI image processing, which often suffers from errors, high costs due to re-scans, and diagnostic delays. This system implements preprocessing techniques, such as median, average, and denoising filters, using a custom FPGA processor developed with System Verilog. In this work, we focused on enhancing image quality and processing speed. For example, the Peak Signal-to-Noise Ratio (PSNR) values for one of the cases are 36.21 dB and 36.03 dB, demonstrating competitive performance compared to Python and MATLAB. The FPGA method also achieves a Mean Squared Error (MSE) as low as 15.57 for one of the cases, highlighting reduced error rates. The results show that the FPGA system achieves superior throughput and reduced error rates, demonstrating its capability to deliver high-quality images in real-time with minimal distortion. Validated using the UVM methodology, the design ensures reliable parallel processing and scalability. This FPGA-based approach significantly improves over traditional MRI image processing methods, making it a more efficient and cost-effective solution for medical imaging applications.

关键词： image quality Filters PSNR image processing Magnetic resonance imaging image edge detection Noise Noise reduction Real-time systems Field programmable gate arrays

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A Fast image Matching Approach in Fatigue Testing of Wall Plate Structures

A Fast Image Matching Approach in Fatigue Testing of Wall Pl...

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IEEE International Conference on Information Communication and Signal processing (ICICSP)

作者： Zhang Wendong Shi Baoquan Chen xianmin Lv Yuanbo National Key Laboratory of Strength and Structural Integrity AVIC Aircraft Strength Research Institute Xi'an China School of Mechano-Electronic Engineering Xidian University Xi'an China

ISBN: (数字)9798350355895

ISBN: (纸本)9798350355901

To address the challenges in motion vector estimation due to local non-uniform deformation of specimens during fatigue tests, this paper proposes an image matching method that combines template sub-image techniques with a Kalman filter. This method employs a mesh motion estimation model, initially using the Kalman filter to predict the matching point positions of mesh nodes. Subsequently, template matching is utilized to achieve precise matching of these nodes. The algorithm is accelerated through GPU-CPU heterogeneous parallel computing technology. Test results indicate that the GPU-accelerated image matching method attains the accuracy of the CPU-based algorithm while significantly reducing processing time, thereby fully meeting the real-time requirements of online image feature matching applications.

关键词： Accuracy Deformation image matching Signal processing algorithms Fatigue Prediction algorithms Vectors Real-time systems Kalman filters Testing

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