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Fλ/d as a predictor of image classification algorithm performance

APPLIED OPTICS 2025年第4期64卷 845-854页

作者： Hixson, Jonathan g. Teaney, Brian Finch, Michael f. Nehmetallah, George Driggers, Ronald US Army Combat Capabil Dev Command DEVCOM C5ISR Ctr RTI Aberdeen Proving Ground NY 21005 USA Catholic Univ Amer EECS Dept 620 Michigan Ave NE Washington DC 20064 USA Univ Arizona Wyant Coll Opt Sci Infrared Syst Grp Tucson AZ 85721 USA

This research studied the effect of variations in a sensor's F lambda/d metric value (FLD) on the performance of machine learning algorithms such as the YOLO (You Only Look Once) algorithm for object classification. The YOLO_v3 and YOLO_v10 algorithms were trained using static imagery provided in the commonly available training dataset provided by Teledyne FLIR systems. image processing techniques were used to degrade image quality of the test dataset also provided by Teledyne FLIR systems, simulating detector-limited to optics-limited performance, which results in a variation of the FLD metric between 0.339 and 7.98. The degraded test set was used to evaluate the performance of YOLO_v3 and YOLO_v10 for object classification and relate the FLD metric to the probability of detection. Results of YOLO_v3 and YOLO_v10 are presented for the varying levels of image degradation. A summary of the results is discussed along with recommendations for evaluating an algorithm's performance using a sensor's FLD metric value. (c) 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： image quality image sensors Imaging systems Imaging techniques Machine learning Sensor performance

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LSHIM: Low-Power and Small-Area Inexact Multiplier for High-Speed Error-Resilient Applications

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IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND systems 2025年第1期15卷 94-104页

作者： Izadi, Azin Jamshidi, vahid Shahid Bahonar Univ Kerman Dept Comp Engn Kerman *** Iran

Numerical computations in various applications can often tolerate a small degree of error. In fields such as data mining, encoding algorithms, image processing, machine learning, and signal processing where error resilience is crucial approximate computing can effectively replace precise computing to minimize circuit delay and power consumption. In these contexts, a certain level of error is permissible. Multiplication, a fundamental arithmetic operation in computer systems, often leads to increased circuit delay, power usage, and area occupation when performed accurately by multipliers, which are key components in these applications. Thus, developing an optimal multiplier represents a significant advantage for inexact computing systems. In this paper, we introduce a novel approximate multiplier based on the Mitchell algorithm. The proposed design has been implemented using the Cadence software environment with the TSMC 45nm standard-cell library and a supply voltage of 1.1v. Simulation results demonstrate an average reduction of 31.7% in area, 46.8% in power consumption, and 36.1% in circuit delay compared to previous works. The mean relative error distance (MRED) for the proposed method is recorded at 2.6%.

关键词： Approximation algorithms Signal processing algorithms Circuits Accuracy Delays Performance evaluation Power demand Arithmetic Adders Energy consumption Approximate multiplier approximate computing Mitchell's multiplication algorithm energy-consumption area delay

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Methods for processing and Understanding image Sequences in Autonomous Navigation Problems

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PATTERN RECOGNITION AND image ANALYSIS 2023年第4期33卷 1104-1128页

作者： Fursov, v. A. Goshin, E. v. Minaev, E. Yu. Zherdev, D. A. Kotov, A. P. Russian Acad Sci Fed Sci Res Ctr Crystallog & Photon Image Proc Syst Inst Branch Samara 443001 Russia Samara Univ Samara 443080 Russia

This article presents the results of research into methods and algorithms for processing image sequences aimed at application in autonomous navigation systems. The methods are grouped in the following areas: pre-processing, generation of 2D and 3D scene models, object recognition. and determination of motion parameters from a sequence of images. The article presents methods and algorithms proposed and researched by the authors of the article over the past decade. Description of the methods and algorithms is accompanied by examples and results of experimental studies.

关键词： digital image processing localization and recognition image matching 3D models fractal compression super resolution visual odometry

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Method for automated assessment of the effectiveness of fruit safety enhancement using an acousto-optical imaging spectrometer

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JOURNAL OF OPTICAL TECHNOLOGY 2024年第7期91卷 452-458页

作者： Batashova, Svetlana s. Zolotukhina, Anastasia a. Guryleva, Anastasia, v Platonova, Natalia b. Kunina, viktoria a. Bauman Moscow State Tech Univ Moscow Russia Russian Acad Sci Sci & Technol Ctr Unique Instrumentat Moscow Russia Russian Acad Sci Subtrop Sci Ctr Soci Krasnodar Regio Russia

Subject of study. This study focuses on the acquisition, processing, and interpretation methods and algorithms for spectral images aimed at evaluating surface defects in fruits. Aim of study. The aim of this study is to develop a method for assessing fruit preservation techniques based on the automatic detection and quantitative evaluation of surface defects using imaging spectroscopy. Method. Spectral images were acquired using an acousto-optical imaging spectrometer with a spectral range of 450-850 nm and a bandwidth of 2.5 nm at a wavelength of 650 nm, with a 5 nm step. For processing the spectral images, well-established operations and algorithms for data enhancement and analysis were employed. These included correction for uneven illumination, correction for spatial and spectral inhomogeneity of the optical system's transmittance coefficient, various image filtering techniques, and threshold binarization. Object classification was based on spectral features. The proposed approach was tested in an experimental study that evaluated the effectiveness of preservation techniques for peaches and nectarines using a treatment that inhibits ethylene production. Main results. A methodology for spectral image acquisition and processing was developed, enabling the automated detection and quantification of surface defects on fruits. An evaluative parameter, defined as the ratio of the defect area to the total surface area of the fruit, was introduced. This parameter allowed for comparison under different experimental conditions. The approving of the approach demonstrated the feasibility of automated defect size determination on fruit surfaces, with a relative error of 11%. Practical significance. The developed data processing algorithms enable regular diagnostics of samples and early identification of defects. The methodology for data acquisition and processing can be extended to devices based on other physical principles for obtaining the spatial distribution of spectral c

关键词： image analysis image registration Imaging techniques Optical systems Spectral properties Transmittance

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Influence of Unequilateral Apertures of Digital Filters Laplacian "Trunced Pyramid" and "Double Pyramid" on the Accuracy of Television Measuring systems

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PROGRAMMING AND COMPUTER SOFTWARE 2024年第3期50卷 238-248页

作者： Rylov, K. A. Kupriyanova, K. S. Kamensky, A. v. Tomsk State Univ Control Syst & Radioelect TUSUR Tomsk 634050 Russia

In the modern world, digital image processing requires increasing the speed of the processing methods and algorithms used. One way to improve performance is to transform spatial filters into filters with a recursively separable form of implementation. The recursion property implies the use of previous output values of a function to form the current sample. The property of separability is understood as division into processing by column and row of a matrix of digital image values. The transformation of spatial filters consists of changing the aperture of the masks into a non-orthogonal (non-equilateral) form, which reduces the number of computational operations and speeds up the processing process, while maintaining its efficiency. The paper presents a description of the non-equilateral apertures of the previously developed Laplacian digital filters "truncated pyramid" and "double pyramid." For non-equilateral apertures, results were obtained for the first time on their use for television measuring systems. From which it can be seen that a "truncated pyramid" Laplacian filter with non-equilateral processing apertures is recommended for use in TIS, since it increases the efficiency of measuring the range to objects of interest while reducing processing time. Based on the results of processing with modified filters, sets of processed images were obtained for each of the 10 original images. For each set of processed images, measurements of the peak signal-to-noise ratio, standard deviation and selection of the optimal central coefficient of the filter mask were carried out, for subsequent assessment of the effectiveness of processing with modified filters. The assessment of the influence of recursively separable Laplacian filters "truncated pyramid" and "double pyramid" with non-equilateral aperture masks on the accuracy of television measurement systems consisted of considering their influence on measuring the distance (from the camera) to the object of interest in the

关键词： digital filters recursively separable filters "truncated pyramid" Laplacian "double pyramid" Laplacian digital image processing television measuring system peak signal-to-noise ratio standard deviation two-dimensional discrete convolution

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Advanced Computer vision Techniques for Accurate Measurement in Unmanned Mobile Robots

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MEASUREMENT SCIENCE REvIEW 2024年第5期24卷 188-192页

作者： Bharathi, v Natraj, N. A. Gopinath, S. Kiruthikaa, R. Kongunadu Coll Engn & Technol Thottiyam India Symbiosis Int Deemed Univ Symbiosis Inst Digital & Telecom Management Pune India Karpagam Inst Technol Coimbatore India KGISL Inst Technol Dept Elect & Commun Engn Coimbatore India

For years, researchers have been studying computer vision, i.e. the ability of artificial intelligence (AI) systems to perceive and interpret visual data like humans. This study is gaining increasing attention as researchers aim to develop tools that automate visual tasks and replicate human visual awareness. However, the interpretation of images is very complex due to the vast amount of multi-resolution information they contain, making the development of AI technologies for visual recognition particularly challenging. This article provides an overview of digital image processing, highlighting the main concepts and introducing key algorithms. These methods are designed to capture, process, and interpret digital images and enable the extraction of important data from real-world environments. We conduct rigorous image processing tests and compare AI-driven recognition systems with human analysis. The results show that computer vision technology significantly outperforms human observation in terms of accuracy and consistency. These results highlight the potential of computer vision to revolutionize various industries by automating complex visual tasks and offer promising future applications in areas such as healthcare, security, and manufacturing. The paper provides valuable insights into current advances in digital image processing and the role of AI in improving visual recognition capabilities, paving the way for further innovation in this area.

关键词： Computer vision digital image processing image recognition data extraction artificial intelligence

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A Mode-Switchable Photonic Radar System for Aerial LSS Targets Detection and Classification

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC systems 2025年第2期61卷 3470-3482页

作者： Selvi, Amalorpava Babu, S. P. K. Raja, Arockia Bazil Periyar Maniammai Inst Sci & Technol Dept Elect & Commun Engn Thanjavur 613403 India Def Inst Adv Technol DIAT Dept Elect Engn RF Photon Lab Pune 411025 India

A mode-switchable continuous wave (CW) and frequency modulated CW (FMCW), photonic radar system with associated signal processing, and artificial intelligent (AI)-based classification algorithms are the need of the hour to accurately detect and classify today's low-altitude slow-speed and smaller size (LSS) targets. We have designed a mode-switchable X-band photonic radar system, whose capabilities are verified with the proposed range/body-Doppler/micro-Doppler imaging techniques and an AI-based classifier;operating six different LSS targets (front-propeller, small-top rotor, big-top rotor, bionic-bird, tiny-helicopter + bionic-bird, and quadcopter). The respective open-field experimental results are discussed/analyzed in terms of detection beat-frequency, range-time map, and range-velocity images in the FMCW mode while the frequency-time images and AI-based six-classes classifications in the CW mode. The obtained results proved that, with the support of designed X-band photonic radar system and proposed signal processing and classification techniques/algorithms, we could able to achieve the 0.1 m spatial resolution with the classification accuracy of 98.5%.

关键词： Radar Radar imaging Photonics Radar detection Radar signal processing Radar cross-sections Optical imaging Accuracy Quadrotors Optical signal processing Deep convolutional neural network (DCNN) low-altitude slow-speed and smaller size (LSS) aerial targets LSS targets accurate detection/classification mode [continuous wave (CW)/ frequency modulated CW (FMCW)] switchable operation photonic X -band radar range-/micro-Doppler (r-D/m-D) image range-time (R-T) image range-velocity (R-v) image

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algorithms of the Tiger and CuneiForm Optical Character Recognition Software

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PATTERN RECOGNITION AND image ANALYSIS 2023年第4期33卷 669-684页

作者： Slavin, O. A. Arlazarov, v. L. Russian Acad Sci Fed Res Ctr Comp Sci & Control Moscow 119333 Russia LLC Smart Engines Serv Moscow 117312 Russia

In this paper, the optical character recognition (OCR) software is considered. The algorithmic solutions of two of the world's best OCR systems, Tiger and CuneiForm, are described in detail. Together with the problems of the geometric identification of characters, the algorithms of image binarization and page fragmentation, combining different recognition, syntactic control, and postrecognition methods, are discussed. The algorithms described in this paper were implemented by a team of mathematicians and software engineers under the supervision of v.L. Arlazarov. This paper contains the references to the published papers of Tiger and CuneiForm OCR software developers, where the described methods and algorithms are described in more detail.

关键词： image processing scientific school

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Medical image Hybrid Watermark Algorithm Based on Frequency Domain processing and Inception v3

ADVANCED INTELLIGENT SYSTEMS

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ADvANCED INTELLIGENT systems 2025年第0期

作者： Fan, Yu Li, Jingbing Bhatti, Uzair Aslam Nawaz, Saqib Ali Chen, Yenwei Hainan Univ Sch Informat & Commun Engn Haikou 570100 Peoples R China Haikou Univ Econ ZX YZ Sch Network Sci Haikou 571127 Peoples R China Hainan Univ State Key Lab Marine Resource Utilizat South China Haikou 570100 Peoples R China Ritsumeikan Univ Grad Sch Informat Sci & Engn Kyoto 5258577 Japan

With the widespread use of digital medical images in recent years, the efficient and secure protection of sensitive data has become an urgent issue. Existing research has mostly focused on optimizing individual techniques, lacking comprehensive solutions that integrate the strengths of different methods. This article proposes a hybrid digital watermarking algorithm for medical images based on frequency domain transformation and deep learning convolutional neural networks. The algorithm combines the advantages of traditional frequency domain watermarking methods and deep learning techniques. Specifically, the algorithm first extracts feature vectors from medical images using discrete wavelet transform and discrete cosine transform, enhancing the robustness of the image watermark. It then integrates an improved Inception v3 network, optimizing the convolutional kernel design, thereby effectively enhancing the robustness of the watermarking process. To further improve the security of the watermark, the Logistic Map is used to scramble and encrypt the watermark information, and a hash function and XOR operation are employed for zero embedding of the watermark. The watermark extraction and decryption process relies on a key provided by a third party, enabling blind extraction of the watermark without requiring the original image. Through extensive experimental data analysis and comparisons with multiple existing algorithms, the results demonstrate that the proposed hybrid watermarking algorithm excels in terms of attack resistance and robustness, significantly improving the security and reliability of medical image watermarking.

关键词： blind extractions digital cosine transforms digital wavelet transforms hybrid algorithms Inception v3 watermark encryptions zero embedding

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LHTAM: Low-power and high-speed approximate multiplier for tiny inexact computing systems

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COMPUTERS & ELECTRICAL ENGINEERING 2025年 123卷

作者： Izadi, Azin Jamshidi, vahid Shahid Bahonar Univ Kerman Dept Comp Engn Kerman Iran

The numerical computations related to certain applications can usually withstand a small amount of error. So in these types of applications, such as data mining, encoding algorithms, image processing, machine learning, signal processing, and other error-resilient applications, accurate computing can be replaced with approximate computing in order to reduce circuit delay and power consumption. In these applications, a certain degree of error is acceptable. Multiplication is a fundamental arithmetic operation in computer systems. However, performing it accurately using multipliers - key components in these systems - can result in increased circuit delay, higher power consumption, and greater use of area. Therefore, presenting an optimal multiplier would be considered as a significant advantage for inexact computing systems. In this paper, we propose a new Mitchell algorithm-based approximate multiplier that applied error-reduction factors can be used. The proposed design has been implemented in the Cadence software environment by using TSMC 45 nm standard-cell library and a supplied voltage of 1.1v. The simulation results indicate an average reduction of 31.7% in area, 64.7% in energy, and 36.1% in circuit delay relative to those achieved in previous works. The mean relative error distance (MRED) of the proposed method is 2.6%.

关键词： Approximate multiplier Approximate computing Mitchell's multiplication algorithm Energy-consumption Area Delay

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