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Real-Time Detection and Monitoring of Oxide Layer Formation in 1045 Steel Using Infrared Thermography and Advanced image processing algorithms

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MATERIALS 2025年第5期18卷 954-954页

作者： Morales-Cervantes, Antony Vergara-Hernandez, Hector Javier Guevara, Edgar Tellez-Martinez, Jorge Sergio Chavez-Campos, Gerardo Marx TecNM Inst Tecnol Morelia Div Estudios Posgrad & Invest Maestria Ciencias Ingn Elect MCIE Ave Tecnol 1500 Morelia 58120 Mexico Univ Autonoma San Luis Potosi Fac Sci San Luis Potosi 78294 Mexico Univ Autonoma San Luis Potosi Coordinac Innovac & Aplicac Ciencia & Tecnol CIACY San Luis Potosi 78210 Mexico

This study addresses the challenge of monitoring oxide layer formation in 1045 steel, a critical issue affecting mechanical properties and phase stability during high-temperature processes (900 degrees C). To tackle this, an image processing algorithm was developed to detect and segment regions of interest (ROIs) in oxidized steel surfaces, utilizing infrared thermography as a non-contact, real-time measurement technique. Controlled heating experiments ensured standardized data acquisition, and the algorithm demonstrated exceptional accuracy with performance metrics such as 96% accuracy and a Dice coefficient of 96.15%. These results underscore the algorithm's capability to monitor oxide scale formation, directly impacting surface quality, thermal uniformity, and material integrity. The integration of thermography with machine learning techniques enhances steel manufacturing processes by enabling precise interventions, reducing material losses, and improving product quality. This work highlights the potential of advanced monitoring systems to address challenges in industrial steel production and contribute to the sustainability of advanced steel materials.

关键词： high-temperature oxidation AISI 1045 steel infrared thermography image processing algorithms mechanical properties phase stability steel manufacturing

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image processing algorithms of Hartmann Aberration Automatic Measurement System Based on Tensor Product Network

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INTERNATIONAL JOURNAL OF WIRELESS INFORMATION NETWORKS 2019年第3期26卷 158-164页

作者： Chen, Yi-bing Open Univ Maoming Sch Expt Ctr Maoming 525000 Guangdong Peoples R China

The research status and limitations of the evaluation on the sensor performance are analyzed in detail, and the development direction of the evaluation on the performance of the Hartmann Aberration Automatic Measurement System is pointed out. Based on the clarification of the Hartmann Aberration Automatic Measurement System with the operational effectiveness and the difference in the operational effectiveness, the connotation of the Hartmann Aberration Automatic Measurement System with the operational effectiveness is expounded. A kind of image processing algorithms based on the consideration of the Hartmann Aberration Automatic Measurement System is put forward. The membership function is changed to simplify the calculation and reduce processing time. Secondly, the adaptive method based on the Hartmann Aberration Automatic Measurement System is applied to the process of selecting the segmentation threshold value, and the threshold values of different images are obtained to make the segmentation more accurate. The experimental results show that compared with the traditional Pal-King algorithm, the algorithm put forward in this paper can preserve the low grey edge information of the image and reduce the computation time. Therefore, it can be applied to the field of image fuzzy edge detection.

关键词： Words-Hartmann Aberration Automatic Measurement System Effectiveness evaluation image processing algorithms Low grey edge information

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Cross-step parallel confocal image processing algorithms used in spatial domain for synthetic-aperture imaging ladars

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OPTIK 2015年第20期126卷 2523-2528页

作者： Hou, Peipei Zhi, Ya'nan Sun, Jianfeng Liu, Liren Chinese Acad Sci Shanghai Inst Opt & Fine Mech Key Lab Space Laser Commun & Detect Technol Shanghai 201800 Peoples R China

Two-dimensional (2D) step parallel confocal image processing algorithm for synthetic aperture imaging ladar (SAIL) is proposed. The feature of the algorithm is the collected data are confocal imaged in space domain by 2D Fourier transform. The collected data are first expressed by separation of variables and time-domain data are translated into a spatial coordinate expression suitable for space optical conversion, compensated with an azimuth quadratic phase and then imaged in space domain by 2D Fourier transform. Functions of the algorithm for SAIL with rectangular apertures is described and analyzed in terms of continuous variables and functions. Then the position of the imaging point is given. The technique is a new, one-step confocal imaging method for ladar echo signal. The confocal image processing is simplified and the imaging time is shortened. The requirement of a ladar image processing system is also reduced. It has a significant advantage in the data processing of synthetic-aperture ladar target echo confocal imaging. (C) 2015 Elsevier GmbH. All rights reserved.

关键词： Synthetic-aperture imaging ladar image processing algorithms Fourier transform Time-to-space domain Spatial domain

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Classification of EEG signals for detection of epileptic seizure activities based on feature extraction from brain maps using image processing algorithms

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IET image processing 2018年第12期12卷 2153-2162页

作者： Jothiraj, Sairamya Nanjappan Selvaraj, Thomas George Ramasamy, Balakrishnan Deivendran, Narain Ponraj Subathra, M. S. P. Karunya Inst Technol & Sci Dept Elect Sci Coimbatore Tamil Nadu India PSG Inst Med Sci & Res Dept Neurol Coimbatore Tamil Nadu India

This study presents a novel feature extraction approach based on image processing algorithms for the automated detection of epileptic seizure activities in brain map representation of electroencephalography (EEG) signal using an efficient classification technique. The proposed technique uses independent component analysis to extract independent components (ICs) from the EEG signal and each extracted IC is transformed into an image termed as brain maps. Two feature extraction techniques namely closed neighbourhood gradient pattern (CNGP) and combined texture pattern (CTP) are propounded for automatic elimination of artefact brain maps. The extracted features are fed into the least square support vector machine (LSSVM) for automatic detection of epileptic brain maps. Extensive experimental result over the existing image processing techniques in literature demonstrates that the texture pattern representations of CNGP and CTP are improved to obtain better features to enhance the performance of texture classification. The obtained result shows that the LSSVM classifier with Gaussian RBF kernel is able to detect the epileptic brain map with a high accuracy rate. The results are reliable and it assists the neurologist to diagnose epileptic signals effortlessly by visually locating the brain area being affected by seizure activities.

关键词： electroencephalography medical signal processing image texture least squares approximations radial basis function networks image classification independent component analysis support vector machines feature extraction medical disorders gradient methods Gaussian processes EEG signal epileptic seizure activities image processing algorithms feature extraction approach brain map representation electroencephalography signal independent component analysis artefact brain maps epileptic brain map texture pattern representations texture classification epileptic signals IC extraction closed neighbourhood gradient pattern least square support vector machine Gaussian RBF kernel

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ISAR geometry, signal model, and image processing algorithms

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IET RADAR SONAR AND NAVIGATION 2017年第9期11卷 1425-1434页

作者： Lazarov, Andon Minchev, Chavdar BFU Comp Sci & Engn Fac 62 San Stefano St Burgas Bulgaria KN Toosi Univ Technol Aerosp Engn Fac Tehran Iran Shumen Univ Tech Fac 115 Univ Ska St Shumen Bulgaria

Inverse synthetic aperture radar (ISAR) technique provides high-resolution images of observed moving objects. However, shadow-occluded effects and noise, which results in lack of fractions of the object geometry, often corrupt ISAR images. To facilitate the image analysis and to solve the target identification problem in most practical applications additional image-processing procedures are strongly required. The aim of the present research is based on ISAR geometry and signal modelling to develop procedures improving quality of images and extract the silhouette contour line of the ISAR image, the main geometric parameter in the target recognition process. The problem is solved in two main stages. First, ISAR geometric parameters are described and expressions for linear frequency modulated signal modelling and imaging are derived. Second, image-processing algorithms for ISAR image improving and contour line extraction are developed. All stages of image-processing and reconstructing algorithms are illustrated by results of numerical experiments.

关键词： synthetic aperture radar radar imaging radar resolution image resolution object recognition ISAR geometry signal model image processing algorithms inverse synthetic aperture radar technique high-resolution images shadow-occluded effects ISAR images image analysis target identification problem silhouette contour line target recognition process linear frequency modulated signal modelling

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The impact of image processing algorithms on digital radiography of patients with metalic hip implants

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PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS 2019年 64卷 238-244页

作者： Tsalafoutas, I. A. Kasviki, K. Samartzis, A. Trimmis, K. Gkeli, M. G. Gen Anticanc Oncol Hosp Athens Agios Savvas Med Phys Dept 171 Alexandras Ave Athens 11522 Greece Reg Gen Hosp Evangelismos Med Phys Lab Ipsilantou 45-47 Athens 10675 Greece Gen Anticanc Oncol Hosp Athens Agios Savvas Radiol Dept 171 Alexandras Ave Athens 11522 Greece

Objective: To investigate the impact of image processing algorithms on image quality of digital radiographs. This study was motivated from a case of a patient with metallic hip implant, where the anatomy around the implant was misrepresented, due to failure of the processing algorithm. Materials & methods: A quality control phantom was imaged using a digital radiographic unit and the standard examination protocol for Pelvis anteroposterior (AP) projection. The original image was reprocessed with all available selections of Diamond View, which is a processing algorithm for optimizing image quality of different anatomic regions. The same procedure was repeated for two other examination protocols, Femur AP and Hip AP, which differ in terms of harmonization kernel and gain, and look up table settings. The whole procedure was repeated with a Pb strip, 2 cm wide and 3 mm thick, positioned close to the right phantom edge, in order to simulate a metallic hip implant. Using imageJ a number of regions of interest (ROIs) were positioned on the phantom images and the impact of processing parameters on certain image characteristics and image quality indices was evaluated. Results: processing parameters have a strong impact on image characteristics, but in terms of image quality, differences between images with and without the implant are small. Exception is the regions in the vicinity of the implant, where larger differences, that could affect diagnosis, were observed. Conclusion: In case of doubt, additional processing with settings which minimize the risk of anatomic misrepresentation should be used.

关键词： Digital radiography image quality image artifacts image processing algorithms

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ELASTIC LOAD-BALANCING FOR image-processing algorithms 1st

ELASTIC LOAD-BALANCING FOR IMAGE-PROCESSING ALGORITHMS

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1ST INTERNATIONAL CONF ON PARALLEL COMPUTATION

作者： MIGUET, S ROBERT, Y ECOLE NORMALE SUPER LYON IMAGINFORMAT PARALLELISME LABF-69364 LYON 7FRANCE

ISBN: (纸本)9783540554370

In this paper, we introduce a data redistribution algorithm which aims at dynamically balancing the workload of image processing algorithms on distributed memory processors. First we briefly review state-of-the-art techniques for load balancing application-specific algorithms. Then we describe the data redistribution technique, which we term ''elastic load balancing'' in a general framework. We demonstrate the usefulness of our redistribution strategy by comparing the efficiency obtained with and without the elastic algorithm for a thinning algorithm which aims at extracting the skeleton of a binary image. We report experimental results obtained with a Supernode machine, based upon reconfigurable networks of 32 Transputers [Nic]. We obtain a speedup of up to 28 over the sequential algorithm, using a Mandelbrot set as a test image. Note that the speedup with a static allocation of the picture was limited to 17 with the same test image, due to the load imbalance among the processors.

关键词： LOAD BALANCING DATA PARTITIONING DATA REDISTRIBUTION DYNAMIC ALLOCATION image processing algorithms DISTRIBUTED MEMORY PROCESSORS

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Performance Analysis of Basic image processing algorithms on GPU

Performance Analysis of Basic Image Processing Algorithms on...

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International Conference on Inventive Systems and Control (ICISC)

作者： Saahithyan, Vigneswaran Suthakar, Somaskandan Univ Jaffna Dept Comp Sci Jaffna Sri Lanka

ISBN: (纸本)9781509047154

image processing could be done in CPU or in Graphical processing Unit (GPU), using sequential programming or parallel programming respectively. Sequential and parallel programming are good in their own paradigm. This paper analyses the performances of various basic image processing algorithms on GPU as well as CPU. Various images with a range of dimensions have been used for the testing purpose. The results show that the usability of the GPU for image processing problems is highly depends on the nature of the problem and also on the size of the problem domain.

关键词： image processing algorithms Graphical processing Unit (GPU) parallel programming CUDA

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Using image processing algorithms for Energy Efficient Routing Algorithm in Sensor Networks

Using Image Processing Algorithms for Energy Efficient Routi...

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Computation World - Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns Conference

作者： Gilg, Marc Yousef, Yaser Lorenz, Pascal Univ Haute Alsace F-68000 Colmar France

ISBN: (纸本)9781424451661

Energy consumption is a major problem in Wireless Sensor Networks (WSNs) because energy resources of sensors are limited. Several protocols have been created to solve this problem. The main objective of these protocols is to maximize the connectivity and network lifetime. Therefore, the choice of the routing algorithm that delivers packets in a wireless sensor network has to be done in a way to preserve energy. This paper presents a novel adaptive routing algorithm based on image processing algorithm, which utilizes the gradient to select a more energy efficient path.

关键词： wireless sensor network image processing algorithms adaptive energy efficient routing Sobel algorithm AODV routing protocol

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The System Operates by Capturing images of the Wall Surface and Applying Advanced image processing algorithms to Analyze the Visual Data 18

The System Operates by Capturing Images of the Wall Surface ...

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18th International Joint Symposium on Artificial Intelligence and Natural Language processing (ISAI-NLP) / 4th International Conference on Artificial Intelligence and Internet of Things (AIoT)

作者： Suksangaram, Wiwit Yimyam, Worawut Phetchaburi Rajabhat Univ Dept Business Informat Management Phetchaburi Thailand

ISBN: (纸本)9798350371215

The main objective of this research is to leverage data and image processing technology to develop a system capable of detecting cracks in walls. The system aims to provide users with a convenient and user-friendly solution by utilizing principles from app development, enabling them to capture photos and assess the presence of wall cracks. To achieve this objective, various image processing techniques are employed, including the use of a Gaussian kernel, grayscale conversion, Sobel edge detection, and thresholding. These techniques are implemented using the Python programming language to develop and apply the image processing algorithms specifically designed for wall crack detection. By employing these techniques, the system can accurately identify cracks and assess the extent of damage in a house using preliminary data. The developed system offers significant advantages for potential homebuyers as it aids in assessing necessary repairs before making a purchase decision. By providing users with a tool to detect and evaluate wall cracks, they can make informed choices regarding the condition of the property and estimate the potential repair costs. This research aims to enhance the accuracy and efficiency of assessing wall cracks, ultimately benefiting individuals in their decision-making process when considering a property purchase.

关键词： Wall Surface Kernal image processing algorithms

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