Digital Picture Processing Research Articles

Development and research of deep neural network fusion computer vision technology

Abstract Deep learning (DL) has revolutionized advanced digital picture processing, enabling significant advancements in computer vision (CV). However, it is important to note that older CV techniques, developed prior to the emergence of DL, still hold value and relevance. Particularly in the realm of more complex, three-dimensional (3D) data such as video and 3D models, CV and multimedia retrieval remain at the forefront of technological advancements. We provide critical insights into the progress made in developing higher-dimensional qualities through the application of DL, and also discuss the advantages and strategies employed in DL. With the widespread use of 3D sensor data and 3D modeling, the analysis and representation of the world in three dimensions have become commonplace. This progress has been facilitated by the development of additional sensors, driven by advancements in areas such as 3D gaming and self-driving vehicles. These advancements have enabled researchers to create feature description models that surpass traditional two-dimensional approaches. This study reveals the current state of advanced digital picture processing, highlighting the role of DL in pushing the boundaries of CV and multimedia retrieval in handling complex, 3D data.

Authorized Automatic Vehicle Allowance System

Abstract: In most organizations, the ongoing vehicle entry registration process for visitors, staff, or students entering the organization includes a security guard checking the driver's identification card or looking for a membership sticker on the vehicle's windscreen, which can easily be lost or stolen. This writing process is tiresome and time-demanding, and it is prone to incorrect notes; additionally, backup and sharing of this vehicle information is difficult due to the data being a physical copy. The goal of the Automatic Authorized Vehicle Allowance System is to create a digital picture processing system with the Raspberry Pi that can be used in an entrance parking system. The Raspberry Pi will identify the car with an ultrasonic sensor and photograph it. The device then processes the picture using digital image processing techniques. The system incorporates various algorithms such as localization, normalization, orientation, segmentation, and optical character recognition (OCR), which examines picture characteristics and forecasts license plate numbers. The obtained number plate information is then cross-checked with records stored in a pre-existing database. An administration is in charge of designating a "whitelist," which is a list of vehicles that can join the suggested system. If the car registration is found in the database, a servo motor circuit connected to a Raspberry Pi will open the gate, and after a monitor delay, the gate will shut. The system is built in such a way that it is simple to apply in a short period of time and is cost-effective.

New Roles for Clinicians in the Age of Artificial Intelligence

Abstract With the rapid developments of digital picture processing, pattern recognition, and intelligent algorithms, artificial intelligence (AI) has been widely applied in the medical field. The applications of artificial intelligence in medicine (AIM) include diagnosis generation, therapy selection, healthcare management, disease stratification, etc. Among the applications, the focuses of AIM are assisting clinicians in implementing disease detection, quantitative measurement, and differential diagnosis to improve diagnostic accuracy and optimize treatment selection. Thus, researchers focus on creating and refining modeling processes, including the processes of data collection, data preprocessing, and data partitioning as well as how models are configured, evaluated, optimized, clinically applied, and used for training. However, there is little research on the consideration of clinicians in the age of AI. Meanwhile, AI is more accurate and spends less time in diagnosis between the competitions of AI and clinicians in some cases. Thus, AIM is gradually becoming a hot topic. Barely a day goes by without a claim that AI techniques are poised to replace most of today’s professionals. Despite huge promise surrounding this technology, AI alone cannot support all the requirements for precision medicine, rather AI should be used in cohesive collaboration with clinicians. However, the integration of AIM has created confusion among clinicians on their role in this era. Therefore, it is necessary to explore new roles for clinicians in the age of AI. Statement of significance With the advent of the era of AI, the integration of medical field and AI is on the rise. Medicine has undergone significant changes, and what was previously labor-intensive work is now being solved through intelligent means. This change has also raised concerns among scholars: Will doctors eventually be replaced by AI? From this perspective, this study elaborates on the reasons why AI cannot replace doctors, and points out how doctors should change their roles to accelerate the integration of these fields, so as to adapt to the developing times.

A New Demagnetization Fault Recognition and Classification Method for DPMSLM

This paper investigates a new method for the demagnetization fault recognition and classification in double-sided permanent magnet synchronous linear motors that are used in linear motion applications. This method is based on time–time-transform (TT) coupled with extreme learning machine (ELM), which are especially suitable for the industrial occasions such as motor batch demagnetization inspection before delivery and periodic maintenance. First, a finite element analysis model with demagnetization faults is built to extract three lines (up-line, center-line, and down-line) magnetic flux density signals. Second, TT is first applied to conduct magnetic signals waveform transformation, and digital picture processing technology is innovatively used to extract the pixel rate of its diagonal elements contour surfaces as the fault feature. Then, machine learning algorithm called ELM is utilized as a classifier to obtain the unique fault labels that can represent the demagnetization occurred positions, sides, and severity types in detail. The validity and superiority of ELM is verified through comparison with back propagation neural network, and probabilistic neural network. Finally, prototype motor experimental platform is designed to confirm the correctness and effectiveness of this proposed method.

Overview of Image Quality Metrics with Perspective to Satellite Image Compression

Image Quality appraisal has been an exacting task in the field of image processing without any satisfactory answer so far. Image quality evaluation tries to quantify a visual quality, an amount of distortion in a given picture. These changes are an inescapable component of any digital picture processing. The correct method of valuing the human-perceived visual quality of the images is the assessment by the human beings. Unfortunately, this process is luxurious, time consuming and cannot be applied in real-time applications. Therefore, there is a demand for a computerized technique that would conceive of the human-perceived visual quality as close as possible. This survey presents an overview about different quality metrics used in-order to assess the image degradation. The few metrics studied are MSE, SNR, PSNR, SSIM, AD, MD, MAE, NK, VSNR, RMSE, UIQM, MSSSIM, FSSIM etc. The image quality metrics are verified with perspective to satellite pictures.

High-Speed Photogrammetry Application for Percussive Rotary Cutting Tests of Deep-Ocean Cobalt-Rich Crusts

The cutting processes of drill rod under different surge pressures, rotate pressures and propulsion forces were recorded by the high-speed camera in the hydraulic percussive rotary cutting tests of deep-ocean cobalt-rich crusts. Meanwhile, the curves of impact vibration, torsional vibration and frame vibration during the cutting processes were plotted by digital picture processing technique. The impact frequency, torsional vibration frequency, torsional vibration amplitude, vibration amplitude of drill rod and the frame were calculated. The photogrammetry results are generally in agreement with the traditional test results. High-speed photogrammetry is a non-contact, wide range application, and high precision measurement, and the cutting process can be described visually and adequately.

Reduction of magnetic confinement fusion data for data mining applications

We develop a practical, structured analysis of multi-channel time series measurements where the main interest lies in the coherent temporal fluctuations and spatial structures and their time dependence. The current approach to most large scale plasma experiments, tokamak and stellarators alike, is the quest for the experimental data taken under optimal conditions for each study. These data are then analysed in detail and sometimes distributed in a reference database such as the tokamak profile database of the ITER 1D Modelling Working Group. While these results are important for our understanding of future fusion devices, they do not provide easy means to support the evidence based on statistical ensembles. The raw data which are not accessible to simple search queries, are usually kept in large data repositories. At H-1, we routinely log the global experimental parameters in a summary database which is stored in a easily accessible database. In order to facilitate statistical analysis and the search for a wide class of magnetic phenomena, we developed a data processing procedure that reduces the raw signal of an array of Mirnov coils at the H-1 into a series of feature descriptors in time-frequency space which are stored in an SQL-accessible database, which can be used together with the summary database. References R. S. Anderssen, F. De Hoog, and M. Hegland, A stable finite difference ansatz for higher order differentiation of non-exact data, Bull. Austral. Math. Soc. 58 (1998), 223--232. S. Beucher, The watershed transformation applied to image segmentation, Conference on Signal and Image Processing in Microscopy and Microanalysis, September 1991, pp. 299--314. T. Dudok de Witt, Enhancement of multichannel data in plasma physics by biorthogonal decomposition, Plasma Physics and Controlled Fusion 37 (1995), no. 2, 117--135, http://stacks.iop.org/0741-3335/37/117. G. H. Golub and C. F. Van Loan, Matrix computations, third ed., Johns Hopkins Studies in the Mathematical Sciences, Johns Hopkins University Press, Baltimore, MD, 1996. MR1417720 (97g:65006) J. H. Harris, M. G. Shats, B. D. Blackwell, W. M. Solomon, D. G. Pretty, S. M. Collis, J. Howard, H. Xia, C. A. Michael, and H. Punzmann, Fluctuations and stability of plasmas in the H-1NF heliac, Nucl. Fusion 44 (2004), 279, doi:10.1088/0029-5515/44/2/008. T. Hastie, R. Tibshirani, and J. H. Friedman, The elements of statistical learning, Springer, August 2001. M. Hegland and R. S. Anderssen, Resolution enhancement of spectra using differentiation, Inverse Problems 21 (2005), no. 3, 915--934, http://stacks.iop.org/0266-5611/21/915. C. Nardone, Multichannel fluctuation data analysis by the singular value decomposition method. Application to MHD modes in JET, Plasma Physics and Controlled Fusion 34 (1992), no. 9, 1447--1465, http://stacks.iop.org/0741-3335/34/1447. A. Rosenfeld and J. L. Pfaltz, Sequential operations in digital picture processing, J. Assoc. Comp. Mach. 13 (1966), 471--494, doi:10.1145/321356.321357. J. Serra, Image analysis and mathematical morphology, Academic Press, Inc., Orlando, FL, USA, 1983. O. Skylar and W. Huber, Image analysis for microscopy screens: Image analysis and processing with EBIimage, R. News 6 (2006), no. 5, 1215, http://CRAN.R-project.org/doc/Rnews/Rnews_2006-5.pdf. R. Stening, T. Reztsova, D. Ivers, J. Turner, and D. Winch, Morning quiet-time ionospheric current reversal at mid to high latitudes, Annales Geophysicae 23 (2005), 385, http://adsabs.harvard.edu/abs/2005AnGeo..23..385S. "The ITER 1D Modelling Working Group", D. Boucher, J. W. Connor, W. A. Houlberg, M. F. Turner, G. Bracco, A. Chudnovskiy, J. G. Cordey, M. J. Greenwald, G. T. Hoang, G. M. D. Hogeweij, S. M. Kaye, J. E. Kinsey, D. R. Mikkelsen, J. Ongena, D. R. Schissel, H. Shirai, J. Stober, P. M. Stubberfield, R. E. Waltz, and J. Weiland, The international multi-tokamak profile database, Nuclear Fusion 40 (2000), no. 12, 1955--1981, http://stacks.iop.org/0029-5515/40/1955. S. Whitehouse, Magick with images, Linux J. (1998), 7, http://www.linuxjournal.com/article/2707.

On Optimisation of Detail Recognition in a Process of Super‐Fast Grinding of Ceramics

AbstractMost of digital picture processing systems are used in mass production. While making use of intelligent systems of standard recognition, digital picture processing can be applied in lot production or small lot production, and their ability to learn enables them to recognize parts of di.erent shapes. In the present paper, a system based on fuzzy logic principles was introduced. It has an application in the automation of the feed of machined elements into the machine working space during machining of ceramics.

A-Convexity

Let S be a subset of R n , and let 0⩽ a⩽1. We call S a-convex if x, y∈S imply a x+(1−a) y∈S . It is incorrectly stated in (Rosenfeld, A., Kak, A.C., 1976. Digital Picture Processing, Academic Press, New York, p. 389; Rosenfeld, A., Kak, A.C., 1982. Digital Picture Processing, second ed. Vol. 2, p. 268) that 1/2-convexity implies convexity. We show that this implication is in fact valid for closed sets and for finite unions of convex sets. We also define fuzzy a-convexity, and show that it implies fuzzy convexity for fuzzy sets whose membership functions are continuous or piecewise constant.

An efficient method for correcting the edge artifact due to smoothing

Spatial smoothing is a common pre-processing step in the analysis of functional brain imaging data. It can increase the signal to noise ratio, and specially designed smoothing filters can be used to selectively increase sensitivity to signals of specific shapes and sizes (Rosenfeld and Kak [1982]: Digital Picture Processing, vol. 2. Orlando, Fla.: Academic; Worsley et al. [1996]: Hum Brain Mapping 4:74–90). Also, some amount of spatial smoothness is required if methods from the theory of Gaussian random fields are to be used (Holmes [1994]: Statistical Issues in Functional Brain Mapping. PhD thesis, University of Glasgow). Smoothing is most often implemented as a convolution of the imaging data with a smoothing kernel, and convolution is most efficiently performed using the Convolution Theorem and the Fast Fourier Transform (Cooley and Tukey [1965]: Math Comput 19:297–301; Priestly [1981]: Spectral Analysis and Time Series. San Diego: Academic; Press et al. [1992]: Numerical Recipes in C: The Art of Scientific Computing, 2nd ed. Cambridge: Cambridge University Press). An undesirable side effect of smoothing is an artifact along the edges of the brain, where brain voxels become smoothed with non-brain voxels. This results in a dark rim which might be mistaken for hypoactivity. In this short methodological paper, we present a method for correcting functional brain images for the edge artifact due to smoothing, while retaining the use of the Convolution Theorem and the Fast Fourier Transform for efficient calculation of convolutions. Hum. Brain Mapping 6:128–136, 1998. © 1998 Wiley-Liss, Inc.

An efficient method for correcting the edge artifact due to smoothing

Spatial smoothing is a common pre-processing step in the analysis of functional brain imaging data. It can increase sensitivity to signals of specific shapes and sizes (Rosenfeld and Kak [1982]: Digital Picture Processing, vol. 2. Orlando, Fla.: Academic; Worsley et al. [1996]: Hum Brain Mapping 4:74-90). Also, some amount of spatial smoothness is required if methods from the theory of Gaussian random fields are to be used (Holmes [1994]: Statistical Issues in Functional Brain Mapping. PhD thesis, University of Glasgow). Smoothing is most often implemented as a convolution of the imaging data with a smoothing kernel, and convolution is most efficiently performed using the Convolution Theorem and the Fast Fourier Transform (Cooley and Tukey [1965]: Math Comput 19:297-301; Priestly [1981]: Spectral Analysis and Time Series. San Diego: Academic; Press et al. [1992]: Numerical Recipes in C: The Art of Scientific Computing, 2nd ed. Cambridge: Cambridge University Press). An undesirable side effect of smoothing is an artifact along the edges of the brain, where brain voxels become smoothed with non-brain voxels. This results in a dark rim which might be mistaken for hypoactivity. In this short methodological paper, we present a method for correcting functional brain images for the edge artifact due to smoothing, while retaining the use of the Convolution Theorem and the Fast Fourier Transform for efficient calculation of convolutions.

Technique Using Thermal Infrared-Imaging for Estimating Populations of Gray Bats

Estimating size of populations of bats during nocturnal emergence from caves relies on techniques of visual counting that are subjective and highly dependent on skill of the observer. A noninvasive technique, using thermal infrared-imaging and digital picture processing, was developed and tested at two caves in northern Alabama. A comparison of estimates between this technique and that of a skilled observer with a night-vision scope revealed a difference of <6%. This semi-automated technique and its applicability are discussed.

A Study of the Gas Flow in the RF Low‐Pressure Supersonic Jet Plasma Chemical System

AbstractWe present results of the experimental study of the gas flow in the RF low‐pressure supersonic‐jet plasma‐chemical reactor. The flow is investigated by using photography with subsequent digital picture processing. The results of the investigations yield valuable data for the physical model of the plasma‐jet system.

Digital distance geometry: A survey

Digital distance geometry (ddg) is the study of distances in the geometry of digitized spaces. This was introduced approximately 25 years ago, when the study of digital geometry itself began, for providing a theoretical background to digital picture processing algorithms. In this survey we focus our attention on theddg of arbitrary dimensions and other related issues and compile an up-to-date list of references on the topic.

A new CCD architecture of high-resolution and sensitivity for color digital still picture

A new charged-coupled device (CCD) architecture developed for building high-resolution and high-sensitivity image sensors suitable for color digital still picture applications is presented. The sensor is based on the interline CCD structure. Both the interline pixels and the vertical charge transfer lines are utilized as light-sensing elements to improve simultaneously the resolution and sensitivity. This device is named the sea-of-photosensor array (SPA-CCD). A camera and supporting digital system were designed and built specifically to evaluate the device. Digital picture processing for white balance adjustment, chromatic correction, and high-frequency luminance was performed to improve color reproduction and picture resolution. An increased light sensitivity and limiting resolutions of 550 horizontal lines and 400 vertical lines on a TV screen were confirmed with an SPA-CCD of the same chip size as a conventional 190-k pixel IT-CCD. The new design of the SPA-CCD overcomes both the sensitivity and the resolution limitations of previous approaches. >

Quadratic curve detection by sampling manner

AbstractThis paper considers the “Segment Pairs Matching” (SPM) method which detects the quadratic curves (e.g., circles and ellipses, etc.) mingled in other patterns such as letters, symbols and straight lines. The SPM method determines the set of sample points lying on the quadratic curves by using the matching condition (named “SPM condition”) which is a restriction on the formation of the sample points. The SPM condition is derived from the algebraic necessary condition under which a quadratic curve can be formed so as to pass through more than five given points. Through theoretical discussions, we clarify the geometrical meaning of the SPM condition and give the generalized formula. The SPM condition plays a geometrical role in deciding whether or not a given curve has a diameter. Then some experimental results show that the SPM condition is approved by digital picture processing and the quadratic curves can be detected with high reliability. Comparison with the Hough Transform demonstrates that the SPM method has the following merits: (i) the processing is done in the picture space; (ii) the operations are very simple (i.e., arithmetical operations); and (iii) the process can be effectively performed from coarse to fine.

Digital picture processing and pattern recognition as applied to magnetic resonance images of diseased human breast tissue

Digital picture processing and pattern recognition as applied to magnetic resonance images of diseased human breast tissue

Difference Equations and a Principle of Double Induction

The theory of partial difference equations, that is, difference equations in two or more variables, has received increasing attention during recent years. This is due to the large number of applications in modem engineering fields such as digital filtering, digital picture processing, seismic data processing, X-ray image enhancement, the enhancement and analysis of aerial photographs for detection of forest fires or crop damage, the analysis of satellite weather photos, and multipass processes (machining operations where the material or workpiece involved is processed by a sequence of passes of the processing tool). Many papers have been published in this area, especially in the two-dimensional linear case (2-D systems). An updated bibliography of these topics may be found in [2]-[5]. Another reason for turning our attention to the forgotten field of partial difference equations (DE) is the use of the finite-difference method for the numerical solution of partial differential equations (PDE). This method transforms many continuous problems into a DE (see [3]-[11]). This fact greatly extends the wide range of possible applications of DE. However, in the study of DE associated with PDE, the emphasis has been put on the approximation of solutions. The analysis of DE properties has been omitted. There have been only a few papers concerning the application of DE to the study of continuous systems described by PDE (see [8]). To illustrate, we present an example of a DE coming from a PDE and one example of a DE modelling a discrete problem.

デジタル画像による速度ベクトルの直接測定法の開発 Ｉ

A new type of flow visualization method with helium bubbles has been developed. This method is based on the ordinary helium bubble method which uses soap bubbles filled with helium gas. The bubbles are injected into the flow in front of the body or injected into the separated region directly. The traces of bubbles are photographed twice in a proper interval. The velocity vectors are calculated by measuring the distance between two traces of each bubble.In the determination of the position of each bubble and distinction of starting point and ending point of traces as a velocity vector digital picture processing technique is used. In the process data are input from video camera and stored microcomputer. Determination of edge of each trace and combination of a pair of traces are processed automatically. The results show a good agreements with previous results. The separated flow fields around two-dimensional wing are visualized qualitatively by the method. The results have proved that the method is quite useful for qualitative flow visualization.

Digital picture processing: a new method to analyse vegetation structure

In this paper a new method for analysis of vegetation structure with a digital picture processing technique is compared with two well-known methods: the point-frequency method and the harvest method. The investigation was carried out in heathland and chalk grassland. Data on vertical distribution measured by the digital picture processing technique were significantly correlated with the data of the point-frequency method and that of dry weight distribution (harvest method). It is concluded that digital picture processing has several advantages with respect to time investment and repetition, and is a good alternative to vegetation structure quantification.