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15th International Conference on Intelligent Human-Computer Interaction (IHCI)

作者： Khamdamov, U. R. Umarov, M. A. Khalilov, S. P. Kayumov, A. A. Abidova, F. Sh. Univ Management & Future Technol Tashkent Uzbekistan Tashkent Univ Informat Technol Samarkand Branch Tashkent Uzbekistan Tashkent Univ Informat Technol Tashkent Uzbekistan

ISBN: (纸本)9783031538292;9783031538308

Due to the improvement in the car manifacture, the rate of road traffic accidents is increasing. To solve these problems, there is loads of attention in research on the development of driver assistance systems, where the main innovation is traffic sign recognition (TSR). In this article, a special convolutional neural network model with high accuracy compared to traditional models is used for TSR. The Uzbek Traffic Sign Dataset (UTSD) applied in the zone of Uzbekistan was created, consisting of 21.923 images belonging to 56 classes. We proposed a parallel computing method for real-time processing of video haze removal. Our utilization can process the 1920 x 1080 video series with 176 frames per second for the dark channel prior (DCP) algorithm. 8.94 times reduction of calculation time compared to the Central processing Unit (CPU) was achieved by performing the TSR process on the Graphics processing Unit (GPU). The algorithms used to detect traffic signs are improved YOLOv5. The results showed a 3.9% increase in accuracy.

关键词： Traffic sign recognition deep learning image dehazing UTSD dataset parallel processing data augmentation

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Energy-Efficient Median Filter Core Architecture for Impulse Noise Removal in Smart Measurement systems

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SN Computer Science 2024年第1期5卷 154页

作者： Nanduri, Sambamurthy Kamaraju, Maddu Department of Electronics and Communication Engineering Seshadri Rao Gudlavalleru Engineering College Andhra Pradesh Gudlavalleru 521356 India

In modern measurement systems, preserving accurate data integrity is essential for reliable and precise measurements. The presence of impulse noise in real-world image data can severely degrade the performance of vision algorithms. Median filtering has proven effective in attenuating impulse noise while retaining edge details. Nevertheless, traditional Median Filter architectures often exhibit high power consumption and hardware resource utilization, limiting their practical applicability in resource-constrained applications. Median filtering has proven effective for impulse noise removal while retaining critical measurement features. Nonetheless, existing architectures for Median Filters may suffer from high power consumption and hardware resource utilization, limiting their suitability for smart measurement systems. To address these limitations, we propose an energy-efficient Median Filter architecture tailored for impulse noise removal in smart measurement systems. The proposed design leverages novel Accumulation of parallel Computing techniques to minimize pixel movements during the filtering process, leading to significant power savings. By utilizing parallel ring counters, selected pixels are kept stationary in specified cells, enabling efficient and rapid median computation. The proposed architecture is implemented using HDL Verilog and thoroughly evaluated on the ZYNQ FPGA platform. Through extensive simulation and synthesis, we assess the architecture’s power consumption and processing speed. The results demonstrate a remarkable 60% reduction in power dissipation, 52% reduction in area and a 2x increase in processing speed compared to existing architectures, making the design well-suited for power-constrained measurement applications. The proposed energy-efficient Median Filter architecture offers an effective and reliable solution for impulse noise removal in smart measurement systems. The design’s optimized power consumption and enhanced processing speed

关键词： Accumulation of parallel computing (APC) Computational measurement FPGA HDL Median filter core

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Highly Accurate and Energy Efficient Binary-Stochastic Multipliers for Fault-Tolerant applications

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IEEE TRANSACTIONS ON CIRCUITS AND systems ii-ExPRESS BRIEFS 2023年第2期70卷 771-775页

作者： Zhang, Yongqiang xie, Lingyun Han, Jie Cheng, xin xie, Guangjun Hefei Univ Technol Sch Microelect Hefei Peoples R China Univ Alberta Dept Elect & Comp Engn Edmonton AB Canada

Stochastic circuits use randomly distributed bit streams to represent numbers, so leading to small areas and low power dissipation. However, it does not only result in a long latency and thus increases energy, but also reduces computing accuracy. In this brief, a design of parallel stochastic multipliers with high accuracy and low energy is proposed. To this end, an algorithm for finding optimal multiplicative bit streams (OpMulbs) is developed for multipliers. Experimental results show that the proposed parallel multipliers using OpMulbs are the most accurate among currently available stochastic multipliers. They also require much less energy with a smaller latency, compared to the others. With a mean squared error of 4.02x10(-6), the proposed 8-bit multiplier shows a 42.18%, 48.15%, 20.35%, and 55.56% reduction in area, power, latency, and energy, respectively, compared to an 8-bit exact binary multiplier. The applications in multiply-accumulate units and image processing algorithms show that the proposed multipliers outperform the state-of-the-art stochastic designs in several considered criteria and binary designs in hardware cost.

关键词： Clocks Hardware Logic gates Costs Thermometers Indexes Energy efficiency Stochastic computing multiplier bitstream computing accuracy hardware cost

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Efficient Plane Segmentation in Depth image Based on Adaptive Patch-Wise Region Growing

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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年第6期10卷 5249-5256页

作者： Zhang, Lantao Niu, Haochen Liu, Peilin Wen, Fei Ying, Rendong Shanghai Jiao Tong Univ Brain Inspired Applicat Technol Ctr BATC Sch Elect Informat & Elect Engn Shanghai 200240 Peoples R China

Plane segmentation algorithms are widely used in robotics, serving key roles in scenarios such as indoor localization, scene understanding, and robotic manipulation. These applications typically require real-time, precise, and robust plane segmentation processing, which presents a significant challenge. Existing methods based on pixel-wise or fix-sized patch-wise operation are redundant, as planar regions in real-world scenes are of diverse sizes. In this paper, we introduce a highly efficient method for plane segmentation, namely Adaptive Patch-wise Region Growing (APRG). APRG begins with data sampling to construct a data pyramid. To avoid redundant planer fitting in large planar regions, we introduce an adaptive patch-wise plane fitting algorithm with the pyramid accessed in a top-down manner. The largest possible planar patches are obtained in this process. Subsequently we introduce a region growing algorithm specially designed for our patch representation. Overall, APRG achieves more than 600 FPS at a 640x480 resolution on a mid-range CPU without using parallel acceleration techniques, which outperforms the state-of-the-art method by a factor of 1.46. Besides, in addition to its speedup in run-time, APRG significantly improves the segmentation quality, especially on real-world data.

关键词： image segmentation Point cloud compression Indexes Fitting Robots Robot sensing systems Data mining Computational efficiency Three-dimensional displays Noise RGB-D perception object detection segmentation and categorization

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Hardware Security of image processing Cores Against IP Piracy Using PSO-Based HLS-Driven Multi-Stage Encryption Fused with Fingerprint Signature

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SN Computer Science 2024年第7期5卷 941页

作者： Sengupta, Anirban Anshul, Aditya Department of Computer Science and Engineering Indian Institute of Technology (IIT) Indore 453552 India

The increasing usage of image processing applications in modern technological environments is driven by their ability to enhance visual quality in diverse applications, from social media to medical imaging. The design of these cores as dedicated application-specific hardware intellectual property (IP) must ensure optimized performance and security. It is crucial to optimize these designs while enhancing their security to create a robust, secure design flow that can provide security against hardware security threats like IP piracy and fraudulent ownership claim. The proposed methodology introduces a low-cost security framework for application-specific hardware systems using an HLS-aided fusion watermarking framework and particle swarm optimization-driven design space exploration (PSO-DSE) process. The proposed approach demonstrates the generation of a multi-stage encryption-based signature along with the IP seller’s fingerprint biometric-based signature, which is further fused to generate the final watermark signature. It allows the embedding of a greater number of secret watermark constraints offering lower probability of coincidence and higher tamper tolerance without incurring design overhead, compared to prior works. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Fingerprint biometric Hardware security HLS image processing applications IP piracy

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An SoC FPGA-based Integrated Real-time image Processor for Uncooled Infrared Focal Plane Array 26

An SoC FPGA-based Integrated Real-time Image Processor for U...

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26th Euromicro Conference on Digital System Design (DSD) / 49th Euromicro Conference on Software Engineering and Advanced applications (SEAA)

作者： Oh, Hyun Woo Choi, Cheol-Ho Cha, Jeong Woo Choi, Hyunmin Han, Joon Hwan Shin, Jung-Ho Infra Technol R&D Ctr Hanwha Syst Seongnam South Korea

ISBN: (纸本)9798350344196

This paper presents an integrated image processor architecture designed for real-time interfacing and processing of high-resolution thermal video obtained from an uncooled infrared focal plane array (IRFPA) utilizing a modern system-on-chip field-programmable gate array (SoC FPGA). Our processor provides a one-chip solution for incorporating non-uniformity correction (NUC) algorithms and contrast enhancement methods (CEM) to be performed seamlessly. We have employed NUC algorithms that utilize multiple coefficients to ensure robust image quality, free from ghosting effects and blurring. These algorithms include polynomial modeling-based thermal drift compensation (TDC), two-point correction (TPC), and run-time discrete flat field correction (FFC). To address the memory bottlenecks originating from the parallel execution of NUC algorithms in real-time, we designed accelerators and parallel caching modules for pixel-wise algorithms based on a multi-parameter polynomial expression. Furthermore, we designed a specialized accelerator architecture to minimize the interrupted time for run-time FFC. The implementation on the xC7Z020CLG400 SoC FPGA with the QuantumRed VR thermal module demonstrates that our image processing module achieves a throughput of 60 frames per second (FPS) when processing 14-bit 640x480 resolution infrared video acquired from an uncooled IRFPA.

关键词： thermal imaging infrared camera image processor architecture non-uniformity correction uncooled infrared focal plane array

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A WEB APPLICATION FOR ULTRASONIC NONDESTRUCTIVE TESTING ANALYSIS 51

A WEB APPLICATION FOR ULTRASONIC NONDESTRUCTIVE TESTING ANAL...

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51st Annual Review of Progress in Quantitative Nondestructive Evaluation (QNDE)

作者： Guarneri, Giovanni A. Pegorini, Vinicius Pipa, Daniel R. Pires, Gustavo P. Nunes, Maria Isabela S. Forlini, Felipe Passarin, Thiago A. R. Univ Tecnol Fed Parana Pato Branco Brazil Univ Tecnol Fed Parana Curitiba Parana Brazil Petrobras SA Rio De Janeiro Brazil

ISBN: (纸本)9780791888162

Identifying and mapping corrosion represents a significant challenge in maintaining oil production systems. Mechanical and chemical phenomena, such as abrasion and hydrogen attack, cause corrosion on the internal surface of pipes. Knowing the dimensions of corrosion enables technicians to make decisions about the structural stability of pipelines under operating conditions. Using ultrasound imaging is a non-destructive approach to assessing the state of internal surfaces. We present a web application for processing ultrasound signals and image reconstruction. However, it can be used in any non-destructive ultrasound inspection application. The software is developed mainly in Python and Typescript, using a different approach than conventional web applications. Instead of using a standard structure, with the front-end running in the browser and the back-end running the data processing on a remote server, our application runs entirely on the browser through Pyodide, a Python distribution for the browser and *** based on WebAssembly whilst the server side only hosts the web application files. The application is divided into modules for (i) graphical interface, (ii) reading inspection files, (iii) signal preprocessing, (iv) estimation of inspection parameters, (v) external surface detection (for inspection by immersion), and (vi) image reconstruction. The web application allows Python script execution and offers a user-friendly interface for running image reconstruction algorithms. This paper describes the development of critical features and indicates the chosen implementation of algorithms. The current state of development is presented, and the next steps toward the ultimate goal of corrosion mapping are defined.

关键词： Ultrasonic NDT image reconstruction Web application

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A 240-FPS In-Column Binarized Neural Network processing in CMOS image Sensors

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IEEE TRANSACTIONS ON CIRCUITS AND systems ii-ExPRESS BRIEFS 2023年第10期70卷 3907-3911页

作者： Jeong, Bohyeok Lee, Jaehwan Lee, Suhyeon Lee, Soyeon Son, Youngdoo Kim, Soo Youn Dongguk Univ Dept Semicond Sci Seoul Campus Seoul 04620 South Korea Dongguk Univ Dept Ind & Syst Engn Seoul Campus Seoul 04620 South Korea Dongguk Univ Data Sci Lab Seoul Campus Seoul 04620 South Korea

This brief presents a CMOS image sensor (CIS) integrated with a binarized neural network (BNN) for face detection in always-on image classification applications. We propose a process variation-immune comparator-based row buffer generating edge images that are inputs of the BNN processor. To reduce the power consumption of column-parallel row buffers, we adopted comparator-based switched capacitor (CBSC) circuits. With a proposed auto-zeroed current source block circuit that operates with low supply voltages, we observed a low variation of rowbuffers' outputs. The measurement results showed that the sigma/mu of the row buffers' output is decreased by 4% while reducing28% of power consumption compared to conventional CBSC-based row buffers. The proposed CIS with an in-column BNN processor having a single channel and two hidden layers was fabricated in a 1-poly 4-metal 110nm CIS process. As a measurement result, we achieved an image classification accuracy is97.75%. Furthermore, the image resolution is 120x120, and the total power consumption of the proposed CIS is 3.78 mW with supply voltages of 2.8 V and 1.5 V at 240 frames per second.

关键词： Always-on binarized neural network CMOS image sensor edge mask row buffer face detection

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Deep Learning-Based Turbulence Mitigation For Long Range imaging 2

Deep Learning-Based Turbulence Mitigation For Long Range Ima...

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Artificial Intelligence for Security and Defence applications ii 2024

作者： Vint, David Di Caterina, Gaetano Kirkland, Paul Lamb, Robert A. Neuromorphic Sensor Signal Processing Lab. EEE Dept. University of Strathclyde United Kingdom Leonardo UK Ltd. Edinburgh United Kingdom

ISBN: (纸本)9781510681200

The distortion caused by turbulence in the atmosphere during long range imaging can result in low quality images and videos. This, in turn, greatly increases the difficulty of any post acquisition tasks such as tracking or classification. The mitigation of such distortions is therefore important, allowing any post processing steps to be performed successfully. We make use of the EDVR network, initially designed for video restoration and super resolution, to mitigate the effects of turbulence. This paper presents two modifications to the training and architecture of EDVR, that improve its applicability to turbulence mitigation: namely the replacement of the deformable convolution layers present in the original EDVR architecture, alongside the addition of perceptual loss. This paper also presents an analysis of common metrics used for image quality assessment and it evaluates their suitability for the comparison of turbulence mitigation approaches. In this context, traditional metrics such as Peak Signal-to-Noise Ratio can be misleading, as they could reward undesirable attributes, such as increased contrast instead of high frequency detail. We argue that the applications for which turbulence mitigated imagery is used should be the real markers of quality for any turbulence mitigation technique. To aid in this, we also present a new turbulence classification dataset that can be used to measure the classification performance before and after turbulence mitigation. © 2024 SPIE.

关键词： image reconstruction

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Digital skin imaging applications, part ii: a comprehensive survey of post-acquisition image utilization features and technology standards

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SKIN RESEARCH AND TECHNOLOGY 2022年第6期28卷 771-779页

作者： Sun, Mary D. Kentley, Jonathan Wilson, Britney W. Soyer, H. Peter Curiel-Lewandrowski, Clara N. Rotemberg, Veronica M. Halpern, Allan C. Icahn Sch Med Mt Sinai New York NY 10029 USA Mem Sloan Kettering Dermatol Serv 530 E 74th St New York NY 10021 USA Chelsea & Westminster Hosp London England Rutgers New Jersey Med Sch Newark NJ USA Univ Queensland Dermatol Res Ctr Diamantina Inst Brisbane Qld Australia Univ Arizona Skin Coll Med Div Dermatol Tucson AZ USA

Background Despite the increasing ubiquity and accessibility of teledermatology applications, few studies have comprehensively surveyed their features and technical standards. Importantly, features implemented after the point of capture are often intended to augment image utilization, while technical standards affect interoperability with existing healthcare systems. We aim to comprehensively survey image utilization features and technical characteristics found within publicly discoverable digital skin imaging applications. Materials and Methods applications were identified and categorized as described in Part I. Included applications were then further assessed by three independent reviewers for post-imaging content, tools, and functionality. Publicly available information was used to determine the presence or absence of relevant technology standards and/or data characteristics. Results A total of 20 post-image acquisition features were identified across three general categories: (1) metadata attachment, (2) functional tools (i.e., those that utilized images or in-app content to perform a user-directed function), and (3) image processing. Over 80% of all applications implemented metadata features, with nearly half having metadata features only. Individual feature occurred and feature richness varied significantly by primary audience (p < 0.0001) and function (p < 0.0001). On average, each application included under three features. Less than half of all applications requested consent for user-uploaded photos and fewer than 10% provided clear data use and privacy policies. Conclusion Post-imaging functionality in skin imaging applications varies significantly by primary audience and intended function, though nearly all applications implemented metadata labeling. Technical standards are often not implemented or reported consistently. Gaps in the provision of clear consent, data privacy, and data use policies should be urgently addressed.

关键词： artificial intelligence clinical imaging digital tools mobile applications quality assurance teledermatology

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