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A 3D-Printed Micro-Optofluidic Chamber for Fluid Characterization and Microparticle Velocity Detection

MICROMACHINES 2023年第11期14卷 2115-2115页

作者： Cutuli, Emanuela Sanalitro, Dario Stella, Giovanna Saitta, Lorena Bucolo, Maide Univ Catania Dept Elect Elect & Comp Sci Engn Via Santa Sofia 64 I-95125 Catania Italy Univ Catania Dept Civil Engn & Architecture Via Santa Sofia 64 I-95125 Catania Italy

This work proposes a multi-objective polydimethylsiloxane (PDMS) micro-optofluidic (MoF) device suitably designed and manufactured through a 3D-printed-based master-slave approach. It exploits optical detection techniques to characterize immiscible fluids or microparticles in suspension inside a compartment specifically designed at the core of the device referred to as the MoF chamber. In addition, we show our novel, fast, and cost-effective methodology, dual-slit particle signal velocimetry (DPSV), for fluids and microparticle velocity detection. Different from the standard state-of-the-art approaches, the methodology focuses on signal processing.rather than image processing. This alternative has several advantages, including the ability to circumvent the requirement of complex and extensive setups and cost reduction. Additionally, its rapid processing.speed allows for real-time sample manipulations in ongoing image-based analyses. For our specific design, optical signals have been detected from the micro-optics components placed in two slots designed ad hoc in the device. To show the devices' multipurpose capabilities, the device has been tested with fluids of various colors and densities and the inclusion of synthetic microparticles. Additionally, several experiments have been conducted to prove the effectiveness of the DPSV approach in estimating microparticle velocities. A digital particle image velocimetry (DPIV)-based approach has been used as a baseline against which the outcomes of our methods have been evaluated. The combination of the suitability of the micro-optical components for integration, along with the MoF chamber device and the DPSV approach, demonstrates a proof of concept towards the challenge of real-time total-on-chip analysis.

关键词： microfluidics micro-optics signal processing lab on a chip DPIV dual-slit

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All-optical image denoising using a diffractive visual processor

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Light(Science & Applications) 2024年第3期13卷 429-445页

作者： Çağatay Işıl Tianyi Gan Fazil Onuralp Ardic Koray Mentesoglu Jagrit Digani Huseyin Karaca Hanlong Chen Jingxi Li Deniz Mengu Mona Jarrahi Kaan Akşit Aydogan Ozcan Electrical and Computer Engineering Department University of CaliforniaLos AngelesCA 90095USA Bioengineering Department University of CaliforniaLos AngelesCA 90095USA California NanoSystems Institute(CNSI) University of CaliforniaLos AngelesCA 90095USA University College London Department of Computer ScienceLondonUnited Kingdom

image denoising,one of the essential inverse problems,targets to remove noise/artifacts from input *** general,digital image denoising algorithms,executed on computers,present latency due to several iterations implemented in,e.g.,graphics processing.units(GPUs).While deep learning-enabled methods can operate non-iteratively,they also introduce latency and impose a significant computational burden,leading to increased power ***,we introduce an analog diffractive image denoiser to all-optically and non-iteratively clean various forms of noise and artifacts from input images–implemented at the speed of light propagation within a thin diffractive visual processor that axially spans<250×λ,whereλis the wavelength of *** all-optical image denoiser comprises passive transmissive layers optimized using deep learning to physically scatter the optical modes that represent various noise features,causing them to miss the output image Field-of-View(FoV)while retaining the object features of *** results show that these diffractive denoisers can efficiently remove salt and pepper noise and image rendering-related spatial artifacts from input phase or intensity images while achieving an output power efficiency of~30–40%.We experimentally demonstrated the effectiveness of this analog denoiser architecture using a 3D-printed diffractive visual processor operating at the terahertz *** to their speed,power-efficiency,and minimal computational overhead,all-optical diffractive denoisers can be transformative for various image display and projection systems,including,e.g.,holographic displays.

关键词： remove rendering holographic

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Low-Power Design of Advanced image processing.algorithms under FPGA in Real-Time Applications 4

Low-Power Design of Advanced Image Processing Algorithms und...

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4th IEEE International Conference on Power, Electronics and Computer Applications, ICPECA 2024

作者： Wang, Yuyao Lamar University Department of Electrical Engineering BeaumontTX United States

ISBN: (纸本)9798350359589

Due to the real-time measurement required for image processing.in practice, image processing.technology is increasingly supplemented by hardware, such as using DSP (digital Signal processing. chips (image processing.specific chips). However, when storing and processing.large amounts of data, using DSP for image processing.also has problems such as slow processing.speed and poor real-time performance of the system. This article combines the embedded cache module in the IP core of FPGA (Field Programmable Gate Array) with the read/write ping-pong structure to store and retrieve image data, in order to save memory space on the chip. The relatively simple algorithm functions and parallel computing of FPGA, combined with a pipeline structure, shorten the image preprocessing.time and solve the problem of poor real-time image processing. The experimental results show that due to the increase in workload, the static power consumption of FPGA algorithm design only increased from lW to 1.242W, while the static power consumption of traditional design increased from 1.009W to 1.578W;The dynamic power consumption of FPGA algorithm design has increased from 1.005W to 1.489W. © 2024 IEEE.

关键词： Field Programmable Gate Array image processing Low-power Design Synchronous Dynamic Random Access Memory

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Study of Camera Efficiency and image Resolution 35

Study of Camera Efficiency and Image Resolution

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35th Conference of Open Innovations Association FRUCT, FRUCT 2024

作者： Jawad, Aqeel Mahmood Alamro, Loai Abdulrazak, Lway Faisal Abdelrahman, Akram AbdelBaqi Bezklubenko, Iryna Al-Rafidain University College Baghdad Iraq Al-Turath University College Baghdad Iraq Cihan University-Sulaimaniya Sulaymaniyah Iraq Al-Noor University College Nineveh Iraq Kyiv National University of Construction and Architecture Kyiv Ukraine

ISBN: (纸本)9789526524610

Background: As imaging technology advances, cinema, photography, computer vision, and image processing.need high-quality visual data. The image quality depends on camera efficiency and ***: This study examines the trade-offs between camera efficiency and image quality concerning camera performance measures (e.g., pixel count, sensor size, dynamic range) and picture resolution. image clarity, detail, and performance are greatly affected by camera resolutions, notably in digital and mobile phone ***: The study tests digital and mobile phone cameras with different resolutions to determine image quality and feature extraction. Additionally, the effects of torch (or flash) use on feature extraction and picture quality are examined to determine how illumination affects camera ***: The importance of camera efficiency in creating high-quality pictures for various applications, including photography and scientific imaging, is highlighted by preliminary findings. The article illuminates the complex link between camera specs and image quality, giving valuable insights to photographers and ***: This study provides insights on enhancing camera efficiency and picture resolution, which may influence imaging equipment, computational image processing. and photographic design. The insights gained should develop camera technology to meet the needs of varied applications that need better picture capture and processing. © 2024 FRUCT.

关键词： Efficiency

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Low Power, High Accuracy Approximate Multiplier for Error-Resilient image processing.Application 8

Low Power, High Accuracy Approximate Multiplier for Error-Re...

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8th IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2024

作者： Harissh, G. Mathumitha, R. Dharini, R.S. Valli, P.A. Mohan, Navya Amrita School of Enginerring Amrita Vishwa Vidyapeetham Dept. of Electronics and Communication Engineering Coimbatore India

ISBN: (纸本)9798350350593

In contemporary times, one of the most crucial requirements for digital signal processing.is high power efficiency. Realizing different multimedia applications, such as processing.images and videos, requires digital signal processing. Multipliers are widely utilized and considered to be one of the most important arithmetic logic units. It is also among the units which utilizes the most power in image processing.applications. When precise processing.is not necessary, approximate computing is an appealing technique to achieve major boosts in area, power, and speed in error-resistant applications. The purpose of this work is to present a unique approximate multiplier design that preserves accuracy metrics while consuming less power. This can serve as a helpful stand-in for precise multipliers. The effectiveness of this multiplier is evaluated based on its power consumption, error metrics, and image processing.application performance. The simulation results demonstrate the effectiveness of the proposed architecture by showing reductions in power consumption of 28.1% and 45.5%, respectively, when compared to the existing approximate and exact multipliers. It also shows comparatively lower values of Normalized mean error distance (NMED) and Mean relative error distance (MRED) proving its efficacy. © 2024 IEEE.

关键词： Multimedia signal processing

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Development of GUI-based deep learning and image processing.system for legume nodule segmentation and classification 34

Development of GUI-based deep learning and image processing ...

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Pattern Recognition and Tracking XXXIV 2023

作者： Salehi, Hassan S. Barchini, Majd Braiser, Kyle Zakeri, Hossein Department of Electrical and Computer Engineering California State University ChicoCA United States Department of Electrical and Computer Engineering University of California DavisCA United States College of Agriculture California State University ChicoCA United States

ISBN: (数字)9781510661691

ISBN: (纸本)9781510661684

Quantification of legumes biological nitrogen fixation (BNF) is normally done via analytical methods that require sampling, drying, grinding, and laboratory processing. These methods are time-consuming, expensive, and are not accessible to growers. The correlation between the BNF quantity and nodule number and nodule mass can be used to develop tools that allow rapid assessments of the BNF. In this work, we developed a graphical user interface (GUI) based deep learning and image processing.system for legume nodule segmentation and classification to determine the characteristics associated with legume nodules using digital images. During image acquisition, the legume root samples were imaged using a smartphone camera and lab-made imaging setup. A total of 1468 digital images were collected from 367 root systems. After the first run of imaging, nodules were separated from the roots, and another image was obtained from the nodules of each sample. For comparison and validations, nodules were manually counted, dried, and weighed. In this study, a categorized image data library was developed and utilized for deep learning and image processing. digital image processing.filters, and image segmentation method were applied to process the digital images of the root systems and determine the number of nodules and provide their characteristics. Deep learning models were used to classify the images into different legume classes. Furthermore, a GUI was successfully developed to simplify the utilization and application of deep learning/digital image processing.algorithms. The preliminary results of this study demonstrate that our deep learning/image analysis system has a great potential to accurately quantify, characterize, and count the nodules and that could be extremely valuable to growers. © 2023 SPIE.

关键词： Deep learning

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A Comparison Between LSTM and Transformers for image Captioning 1

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3rd International Conference on digital Technologies and Applications

作者： Zouitni, Chaimae Sabri, My Abdelouahed Aarab, Abdellah Univ Sidi Mohamed Ben Abdellah Fac Sci Dhar El Mahraz Dept Comp Sci Fes Morocco

ISBN: (数字)9783031298608

ISBN: (纸本)9783031298592;9783031298608

image captioning is the process of generating a textual description of images, which integrates both computer vision and natural language processing. Approaches based on encoder-decoder architectures have been recently proposed to solve image captioning problems. The main objective of this paper is to conduct a comparative study between the two most widely used approaches for natural language processing.tasks, namely, LSTMs and Transformers. We used the Flickr8k dataset as input images. Regarding image feature extraction, we used the VGG16 model. To evaluate the obtained descriptions generated by the models, the BLEU score metric is used to measure the performance of both models. The latter were able to generate grammatically correct and expressive captions.

关键词： image captioning Encoder-Decoder architecture VGG16 LSTM Transformers Attention mechanism Flickr 8k BLEU

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Focusing Algorithm of Automatic Control Microscope Based on digital image processing

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JOURNAL OF SENSORS 2021年第1期2021卷

作者： Zhang, Jing Zhang, Tao Jilin Univ Architecture & Technol Basic Sci Dept Changchun 130114 Jilin Peoples R China FAW Volkswagen Automot Co Ltd Qual Assurance Changchun 130062 Jilin Peoples R China

When performing digital image processing. the most critical technology that affects its use effect is the autofocus technology. With the advancement of science and the development of computer technology, autofocus technology has become more and more widely used in various fields. Autofocus technology is a key technology in robot vision and digital video systems. In order to allow digital image processing.technology to better serve humans, it is necessary to further improve the focus evaluation function algorithm. This article focuses on the imaging principle of defocused images, using different evaluation functions to analyze and process the experimental images to observe the changes in image clarity. Through the introduction and analysis of the existing evaluation function, it can be known that the focus evaluation function will directly affect the quality of digital image processing. Therefore, it is best to choose unimodality, unbiasedness, low noise sensitivity, wide coverage, and a small amount of calculation. For the evaluation function, the Laplacian gradient function is an ideal choice. However, because the current digital image processing.technology is not perfect enough, the focus function is still prone to multiextreme problems when the image is severely defocused and the high-frequency components in the image are missing;the balance between image processing.speed and focus accuracy also still needs to be improved. Therefore, this paper studies the autocontrol microscope focus algorithm based on digital image processing. analyzes the principle of visual image imaging, and makes some improvements to the microscope focus algorithm. Through experiments, it can be seen that the real-time data of the original Laplace function in the edge-obvious target is 76.9, and it reaches 77.6 after improvement. The improved algorithm can better maintain the single-peak state during the focusing process, which improves the image processing.efficiency while ensuring the mea

关键词： Computer graphics

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Research on Data processing.Security System Based on Bio commercial technology and Artificial Intelligence

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Journal of Commercial Biotechnology 2023年第1期28卷 34-42页

作者： Tang, Li Zhao, Zhiyu Li, Biaoqi Xu, Min China Yunnan Power Grid Yunnan Province China

Data security has become an increasingly important concern for organizations and individuals in the digital age. To address this issue, there has been growing interest in using bio-commercial technology and artificial intelligence (AI) to develop innovative security solutions. This paper presents a research study on the development of a data processing.secure new entrants in the market for medical devices in Germany can use the use of biometric data, such as fingerprints, iris scans, and voice recognition, in combination with AI algorithms to enhance the security of data processing. The paper provides an overview of the technical framework and architecture of the proposed system, and evaluates its effectiveness in comparison to traditional security measures. The study uses a combination of quantitative and qualitative research methods, including surveys, interviews, and simulations, to collect and analyze data on the performance, accuracy, and usability of the proposed system. The results suggest that the data processing.security system based on bio-commercial technology and AI is highly effective in preventing unauthorized access and enhancing data protection. The system provides a high level of accuracy, speed, and user-friendliness, making it a viable alternative to traditional security measures. The paper concludes with a discussion of the implications of the study for the field of data security and future research directions. © 2023 ThinkBiotech LLC. All rights reserved.

关键词： Big data

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digital Media image Enhancement Technology based on Data Analysis 2

Digital Media Image Enhancement Technology based on Data Ana...

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2nd International Conference on Data Science and Information System, ICDSIS 2024

作者： Yang, Gongbo Wang, Lin Jinan Preschool Education College College Of Information And Business Shandong Jinan China Jinan Preschool Education College College Of Wang Jinmei Ideological And Political Education Shandong Jinan China

ISBN: (纸本)9798350381665

In recent years, with the rapid development of computer and information technology, image processing.technology is also developing continuously, and has become the object of mutual learning and discussion of computer science, medicine, biology, engineering, information science and other disciplines. In the image processing.system, its processing.process can be divided into three steps: the first is the original image preprocessing. the second is the image feature extraction, the third is the image identification analysis. Among them, the image preprocessing.link, that is, the image enhancement. Therefore, before the analysis of the image, we must first improve the quality of the image, then we need to use image enhancement. image enhancement is an important basic image processing.method, its goal is to process an image, make it highlight some specific information, weaken or remove some unnecessary information, so as to obtain better visual effect and use, or transform it into a format more suitable for human or machine analysis and processing. Based on the above problems, this paper discusses how to construct the image super-resolution reconstruction model through the Convolutional Neural Networks (CNN) algorithm and the attention mechanism, and analyzes the performance of other algorithm models through experiments. The results show that the image reconstruction time based on CNN-AM is only 20.7 s, which is shorter than other algorithms. © 2024 IEEE.

关键词： image enhancement

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