Relevant bibliographies by topics / Image defects

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Image defects'

Author: Grafiati
Published: 28 May 2022
Last updated: 30 July 2025

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Journal articles on the topic "Image defects"

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Lee, Wei-Chen, and Pei-Ling Tai. "Defect Detection in Striped Images Using a One-Dimensional Median Filter." Applied Sciences 10, no. 3 (2020): 1012. http://dx.doi.org/10.3390/app10031012.

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Defect detection is a key element of quality assurance in many modern manufacturing processes. Defect detection methods, however, often involve a great deal of time and manual work. Image processing has become widely used as a means of reducing the required detection time and effort in manufacturing. To this end, this study proposes an image-processing algorithm for detecting defects in images with striped backgrounds—defect types include scratches and stains. In order to detect defects, the proposed method first pre-processes images and rotates them to align the stripes horizontally. Then, th
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Zhang, Na, Gang Yang, Fan Hu, Hua Yu, Jingjing Fan, and Siqing Xu. "A Novel Adversarial Deep Learning Method for Substation Defect Image Generation." Sensors 24, no. 14 (2024): 4512. http://dx.doi.org/10.3390/s24144512.

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The presence of defects in substation equipment is a major factor affecting the safety of power transmission. Therefore, timely and accurate detection of these defects is crucial. As intelligent inspection robots advance, using mainstream object detection models to diagnose surface defects in substation equipment has become a focal point of current research. However, the lack of defect image data is one of the main factors affecting the accuracy of supervised deep learning-based defect detection models. To address the issue of insufficient training data for defect images with complex backgroun
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Chen, Ming Fu, Chih Chung Chou, Chun Jie Lien, and Rui Cian Weng. "An Optical Inspection System for Chip Defects Using a High Rate Line Scanner." Applied Mechanics and Materials 574 (July 2014): 462–67. http://dx.doi.org/10.4028/www.scientific.net/amm.574.462.

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Based on a line scan imager, we propose anew defect inspection system to precisely identify defects with size of greater than criteria from chip backside. Only a corresponding raw image is acquiredfor each chip,and using anopto-mechanical device with very low geometry distortion to make it feasible to neglectprocesses of image calibration and mosaic. Defect inspection is based on a binary chip edge image and a novel methodof using edge pixels statistic. Thus defect size of crack, chipping and glue can be inspected quantitatively and efficiently.From test results by integrating inspection syste
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Dr. Avinash S, Dr. Prathapchandra, and Mr. Ramachandra. "Fault Detection in Printed Circuit Board (PCB) using Image Subtraction Method." International Journal of Innovative Technology and Exploring Engineering 13, no. 7 (2024): 1–6. http://dx.doi.org/10.35940/ijitee.g9906.13070624.

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Fault detection in PCBs is a important task in the electronics industry to ensure the consistency and performance of electronic devices. One common approach for detecting defects in PCBs is the subtraction method, which involves subtracting a reference image of a defect-free PCB from an image of a PCB with defects. The resulting image gives the differences between the two images, making it easier to detect and classify defects. In this work, a defect detection system for PCBs using the subtraction method using MATLAB is proposed. The research work uses publicly available PCB defect datasets to
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Dr., Avinash S. "Fault Detection in Printed Circuit Board (PCB) using Image Subtraction Method." International Journal of Innovative Technology and Exploring Engineering (IJITEE) 13, no. 7 (2024): 1–6. https://doi.org/10.35940/ijitee.G9906.13070624.

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<strong>Abstract: </strong>Fault detection in PCBs is a important task in the electronics industry to ensure the consistency and performance of electronic devices. One common approach for detecting defects in PCBs is the subtraction method, which involves subtracting a reference image of a defect- free PCB from an image of a PCB with defects. The resulting image gives the differences between the two images, making it easier to detect and classify defects. In this work, a defect detection system for PCBs using the subtraction method using MATLAB is proposed. The research work uses publicly avai
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Zhou, Yang, Lijuan Zhu, and Dong Ma. "Research on Traditional Image Segmentation Method Based on Oil Drilling Pipe Defects." Journal of Physics: Conference Series 2639, no. 1 (2023): 012057. http://dx.doi.org/10.1088/1742-6596/2639/1/012057.

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Abstract This study explores the feasibility and efficacy of conventional image seg-mentation technology in diagnosing failures in oil drilling pipe images. Simultaneously, it envisions an intelligent approach to diagnose defects in oil drilling pipes. The present paper examines and scrutinizes traditional image segmentation methods in light of the characteristics of oil drilling pipe defect images. It devises experiments tailored for these defect images and employs various traditional image segmentation methods to facilitate comparison and evaluation. The experimental findings illustrate that
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Guo, LongYuan, ShiNan Li, Wenjing Hu, et al. "Sub-Pixel Level Defect Detection Based on Notch Filter and Image Registration." International Journal of Pattern Recognition and Artificial Intelligence 32, no. 06 (2018): 1854016. http://dx.doi.org/10.1142/s0218001418540162.

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General machine vision algorithms are difficult to detect LCD sub-pixel level defects. By studying the LCD screen images, we found that the pixels in the LCD screen are regularly arranged. The spectrum distribution of LCD images, which is obtained by the Fourier transform, is relatively consistent. According to this feature, a method of sub-pixel defect detection based on notch filter and image registration is proposed. First, we take a defect-free template image to establish registration template and notch-filtering template; then we take the defect images for image registration with registra
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Gao, Pengyu, Xin Yan, Jinpeng He, Haojun Yang, Xindu Chen, and Xiangdong Gao. "Processing of Eddy Current Infrared Thermography and Magneto-Optical Imaging for Detecting Laser Welding Defects." Metals 15, no. 2 (2025): 119. https://doi.org/10.3390/met15020119.

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Infrared (IR) magneto-optical (MO) bi-imaging is an innovative method for detecting weld defects, and it is important to process both IR thermography and MO imaging characteristics of weld defects. IR thermography and MO imaging can not only run simultaneously but can also run separately in special welding processes. This paper studies the sensing processing of eddy current IR thermography and MO imaging for detecting weld defects of laser spot welding and butt joint laser welding, respectively. To address the issues of high-level noise and low contrast in eddy current IR detection thermal ima
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Wei, Bing, Lei Gao, Xue-song Tang, and Kuangrong Hao. "Multi-Class Object Learning with Application to Fabric Defects Detection." AATCC Journal of Research 8, no. 1_suppl (2021): 165–72. http://dx.doi.org/10.14504/ajr.8.s1.20.

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Deep convolutional neural networks (CNNs) have shown great success in single-class fabric image detection. However, real-world fabric defect images generally contain several types of defects in one image. Accurately recognizing and classifying multi-class fabric defect images is still an unsolved issue due to the complexity of intersected defects, as well as difficulty in distinguishing small-size defects. To address these challenges, this study develops a methodology based on the deep learning feature pyramid networks (FPN) approach to detect multi-class fabric defects. To evaluate the propos
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Riza, Dimas Firmanda Al, Tetsuhito Suzuki, Yuichi Ogawa, and Naoshi Kondo. "External Defects and Soil Deposits Identification on Potato Tubers using 2CCD Camera and Principal Component Images." Industria: Jurnal Teknologi dan Manajemen Agroindustri 12, no. 2 (2023): 143–55. http://dx.doi.org/10.21776/ub.industria.2023.012.02.4.

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Precise recognition of potato external defects and the ability to identify defects and non-defect areas are in demand. Common scab represents a significant issue that requires detection, yet identifying the extent of common scab infection remains challenging when using a standard RGB camera. In this research, a 2CCD camera system that could obtain a set of RGB and near-infrared images, which could enhance defect detection, has been used. Image segmentation strategies based on a single principal component image and the principal component pseudo-colored image have been proposed to identify exte
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Dissertations / Theses on the topic "Image defects"

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Louridas, Efstathios. "Image processing and analysis of videofluoroscopy images in cleft palate patients." Thesis, University of Kent, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267392.

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Palmquist, Jonathan. "Detecting defects on cheese using hyperspectral image analysis." Thesis, Umeå universitet, Institutionen för fysik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-172695.

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Defects such as mold and bacterial stains can appear on cheese. Manually detecting defects is a time-consuming, cost-ineffective, and ergonomically unsatisfactory process for a dairy because the quality technicians must inspect each cheese before packaging. Instead, dairies would prefer an automatic detection system, but it is unclear whether reliable options are available. One potential approach is hyperspectral image analysis, which can interpret and classify chemical information from a sample. We collected hyperspectral images from a dairy using a short-wave infrared (SWIR) camera and compa
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Al-Eidarous, Mustafa H. "Image processing : techniques for locating defects on shirt collars." Thesis, University of Hull, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.301339.

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Wi, Huiju. "Evaluating Defects of Bridge Elements Using an Image Processing Approach." Thesis, Griffith University, 2014. http://hdl.handle.net/10072/366670.

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The total expenditure on bridge maintenance/rehabilitation and improvement for the year 2010-11 in Australia was AUD1.2 billion. This was a 67% rise in ten years. The efficient use of public funds for the structural integrity of bridge networks requires an effective bridge asset management technology. For effective asset management, many bridge authorities have implemented Bridge Information System (BIS) or Bridge Management System (BMS) to manage their routine inspection information. The success of a BMS is highly dependent on the quality of bridge inspection results and accurate est
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Yang, Hsien-Min 1957. "IC defect detection using color information and image processing." Thesis, The University of Arizona, 1988. http://hdl.handle.net/10150/276831.

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Most current commercial automated IC inspection systems use gray-level or binary images for IC defect detection in spite of the fact that color permits defect detection where gray-level information is insufficient. Three color image processing techniques including the spectral-spatial clustering, principal components, and hue-saturation-value (HSV) color features have been investigated to evaluate the usefulness of color for IC defect detection. The AMOEBA spectral-spatial clustering algorithm, an un-supervised color segmentation approach, with a sequence of image processing procedures resulte
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Abdellatif, Abeer Moustafa. "A study of developmental defects of enamel using clinical indices and image analysis." Thesis, University of Sheffield, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.247151.

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Jorgenson, Todd F. "Comparison of two imaging modalities : F-speed film and digital images for detection of osseous defects in patients with vertical bone defects /." Oklahoma City : [s.n.], 2003.

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Wei, Guo-Feng. "An image quality model based on the influence of Mura defects in TFT-LCDs." Thesis, University of Leeds, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.581866.

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Mura is a type of defect on LCD's that affects image quality. Due to its subtle nature - gradually and non-uniformly changes in lightness within a specific area, how Mura defects can be effectively inspected and objectively graded has been an issue in the LCD manufacturing industry for many years. Although many studies using different approaches to the Mura detection issue have been carried out, there is still a lack of reliable standard and methods that can be fully adopted in the industry and replace the human eye in the inspection work. Based on demand from the LCD industry, a uniform Mura
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GNANAPRAKASAM, PRADEEP. "CHARACTERIZATION OF SEED DEFECTS IN HIGHLY SPECULAR SMOOTH COATED SURFACES." UKnowledge, 2004. http://uknowledge.uky.edu/gradschool_theses/318.

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Many smooth, highly specular coatings such as automotive paints are subjected to considerable performance demands as the customer expectations for appearance of coatings are continually increasing. Therefore it is vital to develop robust methods to monitor surface quality online. An automated visual assessment of specular coated surface that would not only provide a cost effective and reliable solution to the industries but also facilitate the implementation of a real-time feedback loop. The scope of this thesis is a subset of the inspection technology that facilitates real-time close loop con
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Johnson, Christopher Ian. "Image processing techniques for the detection and characterisation of features and defects in railway tracks." Thesis, Manchester Metropolitan University, 2013. http://e-space.mmu.ac.uk/332148/.

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This thesis describes the research that led to the development of a machine vision system in collaboration with TATA, UK and Sheffield Supertram. This was part of a European initiative for Predictive Maintenance employing non-intrusive inspection and data analysis known as PM’n’Idea. The hardware and software design, construction, and evaluation of a prototype for predictive maintenance are presented. The prototype was tested on Sheffield and Warsaw’s tram systems. The prototype has been designed with due account of a specified set of environmental constraints such as a high level of vibration
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Books on the topic "Image defects"

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Louban, Roman. Image Processing of Edge and Surface Defects. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00683-8.

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Chung, Michael J. Detection of fuse defects by image processing methods. Materials Research Laboratory, 1988.

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1950-, Mickelson Alan Rolf, ed. Defect recognition and image processing in semiconductors 1995: Proceedings of the sixth international conference, held in Boulder, Colorado, 3-6 December 1995. Institute of Physics Pub., 1996.

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International Conference on Defects--Recognition, Imaging and Physics in Semiconductors (8th 1999 Narita-shi, Japan). Defects--recognition, imaging and physics in semiconductors 1999: Proceedings of the eighth International Conference on Defects--Recognition, Imaging and Physics in Semiconductors, Narita, Japan, September 15-18, 1999. Elsevier, 2000.

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International Conference on Defects--Recognition, Imaging and Physics in Semiconductors (8th 1999 Narita-shi, Japan). Defects--recognition, imaging and physics in semiconductors 1999: Proceedings of the eighth International Conference on Defects--Recognition, Imaging and Physics in Semiconductors, Narita, Japan, September 15-18, 1999. Elsevier, 2000.

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J, Jiménez, and International Symposium on Defect Recognition and Image Processing in III-V Compounds (5th : 1993 : Santander, Spain), eds. Defect recognition and image processing in semiconductors and devices: Proceedings of the fifth international conference, Santander, Spain, 6-10 September 1993. Institute of Physics Pub., 1994.

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International, Symposium on Defect Recognition and Image Processing in III-V. Compounds (3rd 1989 Tokyo Japan). Defect recognition and image processing in III-V compounds, III: Proceedings of the Third International Symposium on Defect Recognition and Image Processing in III-V Compounds (DRIP III), Tokyo, Japan, 22-25 September 1989. North Holland, 1990.

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International Symposium on Defect Recognition and Image Processing in III-V Compounds (2nd 1987 Monterey, Calif.). Defect recognition and image processing in III-V compounds, II: Proceedings of the Second International Symposium on Defect Recognition and Image Processing in III-V Compounds (DRIP II), Monterey, California, April 27-29, 1987. Elsevier, 1987.

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P, Fillard J., ed. Defect recognition and image processing in III-V compounds: Proceedings of the International Symposium on Defect Recogition and Image Processing in III-V Compounds (DRIP 1985), Montpellier, France, July 2-4, 1985. Elsevier, 1985.

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International Conference on Defect Recognition and Image Processing in Semiconductors (7th 1997 Templin, Germany). Defect recognition and image processing in semiconductors 1997: Proceedings of the 7th International Conference on Defect Recognition and Image Processing in Semiconductors (DRIP VII) held in Templin, Germany, 7-10 September 1997. Institute of Physics Pub., 1998.

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Book chapters on the topic "Image defects"

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Goldstein, Joseph I., Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. "Image Defects." In Scanning Electron Microscopy and X-Ray Microanalysis. Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-6676-9_9.

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Gordon, Sonya G. "Septal Defects." In Veterinary Image-Guided Interventions. John Wiley & Sons, Ltd, 2015. http://dx.doi.org/10.1002/9781118910924.ch63.

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Li, Wei, Xin’an Yuan, Jianming Zhao, Xiaokang Yin, and Xiao Li. "Design and Testing of High-Resolution Probe Arrays Using Alternating Current Field Measurement Technique." In Alternating Current Field Measurement Technique for Detection and Measurement of Cracks in Structures. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-7255-1_5.

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AbstractFor the large space of sensor array in the alternating current field measurement (ACFM) probe, the spatial resolution of the measured distorted magnetic image is low above defects. As a result, the accurate morphology of defects cannot be reconstructed. In this paper, a novel ACFM probe array and testing system are set up based on the high resolution TMR magnetic field sensor array for the high-resolution imaging of distorted magnetic field. The finite element simulation model of ACFM is established. The induced electromagnetic field distortion law around the different defects is analy
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Fridrich, Jessica. "Sensor Defects in Digital Image Forensic." In Digital Image Forensics. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-0757-7_6.

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Nakakura, Yuta, Kosuke Temizu, Mana Nishino, and Ryosuke Nakajima. "A Case Study on Evaluation of Defect Characteristics for Practical Application of Appearance Inspection Work Support System Utilizing Deep Learning." In Lecture Notes in Mechanical Engineering. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-28839-5_60.

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AbstractTo prevent outflow of defective products to customers, many manufacturing industries have focused not only on processing and assembling, but also on product inspection. In appearance inspection, a work support system using deep learning has been proposed, and its usefulness was experimentally shown in model images of industrial product in recent years. Therefore, in this study, aiming for practical application of work support system, the relationship between the lighting angles and the visibility of defects is experimentally evaluated using 80 actual automobile parts as a case study. A
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Dirik, Ahmet Emir. "Source Attribution Based on Physical Defects in Light Path." In Digital Image Forensics. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-0757-7_7.

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Lehr, Jan, Jan Philipps, Alik Sargsyan, Martin Pape, and Jörg Krüger. "AD3: Introducing a Score for Anomaly Detection Dataset Difficulty Assessment Using VIADUCT Dataset." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-73113-6_26.

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AbstractThe field of visual Industrial Anomaly Detection (IAD) has brought forth many new semi-supervised learning methods in recent years. At the same time, there have been few new datasets for benchmarking the methods. The most popular dataset is MVTec-AD dataset, because of its diversity of categories and availability of industrial objects. But many methods already achieve AUROC scores of more than 99 % on the MVTec-AD dataset. The defects of the categories that the dataset provides appear to be easily detectable. Furthermore, there is no existing approach to statistically describe the defe
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Lehr, J., C. Briese, S. Mönchinger, O. Kroeger, and J. Krüger. "Challenges of Automatic Optical Inspection of Used Turbine Blades with Convolutional Neural Networks." In Lecture Notes in Mechanical Engineering. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-77429-4_34.

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AbstractThis paper presents an automatic optical inspection task for used turbine blades. The defects arising are very small and occur very rarely. The paper analyzes to what extent state of the art deep learning methods of image processing help to solve the inspection tasks. A total of 34 different turbine blades were acquired image-wise for this work. For the localization and classification of the defects, detection methods such as YOLOv7 were used on the one hand, and segmentation methods such as Mask R CNN and QueryInst on the other. Despite a very small amount of data, the methods can be
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Mery, Domingo. "Crossing Line Profile: A New Approach to Detecting Defects in Aluminium Die Casting." In Image Analysis. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-45103-x_96.

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Luo, Dan, Joseph M. Gattas, and Poah Shiun Shawn Tan. "Real-Time Defect Recognition and Optimized Decision Making for Structural Timber Jointing." In Proceedings of the 2020 DigitalFUTURES. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4400-6_4.

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AbstractNon-structural or out-of-grade timber framing material contains a large proportion of visual and natural defects. A common strategy to recover usable material from these timbers is the marking and removing of defects, with the generated intermediate lengths of clear wood then joined into a single piece of full-length structural timber. This paper presents a novel workflow that uses machine learning based image recognition and a computational decision-making algorithm to enhance the automation and efficiency of current defect identification and re-joining processes. The proposed workflo
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Conference papers on the topic "Image defects"

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Zhao, Rongxin, Feng Wang, Huayong Wu, and Zijie Zhou. "Recognition of Apparent Defects in Bridge Cable Bundle Wraps Based on Deep Learning Algorithms." In IABSE Symposium, Tokyo 2025: Environmentally Friendly Technologies and Structures: Focusing on Sustainable Approaches. International Association for Bridge and Structural Engineering (IABSE), 2025. https://doi.org/10.2749/tokyo.2025.1992.

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&lt;p&gt;Cables, as the main load-bearing components, have a profound impact on the lifespan of cable- structured bridges. With the rapid development of bridge construction in China, collapses due to cable fractures occur from time to time. Traditional methods for detecting apparent defects of cable sheaths through manual inspection are labor-intensive and involve certain safety risks, failing to meet the demands of the new era for cable defects detection. This paper employs mobile detection equipment to collect and locate high-definition images of cable sheaths, constructs an in-service bridg
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Choudhary, Binod Kumar, Atul Dadhich, and Asha Rajiv. "Detection of Defects in Processed Metals Through Image Analysis." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10725974.

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Zhang, ZiYe, and XiangQuan Chang. "Express packaging defects detection model based on YOLOv8." In 4th International Conference on Image Processing and Intelligent Control (IPIC 2024), edited by Kelin Du and Azlan bin Mohd Zain. SPIE, 2024. http://dx.doi.org/10.1117/12.3038509.

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Guo, Jing, Zhen Liu, Zheng Zhang, Zhiqiang Bai, Yaodong Wang, and Baoqing Guo. "Research on rail image acquisition and defects intelligent recognition technology." In Seventeenth International Conference on Digital Image Processing (ICDIP 2025), edited by Xudong Jiang, Jindong Tian, Ting-Chung Poon, and Zhaohui Wang. SPIE, 2025. https://doi.org/10.1117/12.3073228.

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Wu, Mingtao, Vir V. Phoha, Young B. Moon, and Amith K. Belman. "Detecting Malicious Defects in 3D Printing Process Using Machine Learning and Image Classification." In ASME 2016 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/imece2016-67641.

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3D printing, or additive manufacturing, is a key technology for future manufacturing systems. However, 3D printing systems have unique vulnerabilities presented by the ability to affect the infill without affecting the exterior. In order to detect malicious infill defects in 3D printing process, this paper proposes the following: 1) investigate malicious defects in the 3D printing process, 2) extract features based on simulated 3D printing process images, and 3) an experiment of image classification with one group of non-defect infill image and the other group of defect infill training image f
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Ouidadi, Hasnaa, Boyang Xu, and Shenghan Guo. "Defect Segmentation From X-Ray Computed Tomography of Laser Powder Bed Fusion Parts: A Comparative Study Among Machine Learning, Deep Learning, and Statistical Image Thresholding Methods." In ASME 2023 18th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/msec2023-104387.

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Abstract Internal defects, e.g., lack of fusion and porosity, are major quality concerns in Laser Powder Bed Fusion (L-PBF). In post-process part inspection, X-ray Computed Tomography (XCT) is used to scan the part to reveal the defective regions inside. 2-dimensional XCT images are obtained showing the part’s cross-section at different heights (layers). Segmenting the defects from raw XCT images is necessary to locate the defected regions, evaluate the part’s quality, and enable root cause analysis. This study proposes two methods for defect segmentation, one is based on deep learning (DL) an
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Barone, Massimiliano. "Image Wafer Inspection based on Template Matching." In 10th International Conference on Advances in Computing and Information Technology (ACITY 2020). AIRCC Publishing Corporation, 2020. http://dx.doi.org/10.5121/csit.2020.101505.

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This paper presents a template matching technique for detecting defects in VLSI wafer images. This method is based on traditional techniques of image analysis and image registration, but it combines the prior art of image wafer inspection in a new way, using prior knowledge like the design layout of VLSI wafer manufacturing process. This technique requires a golden template of the patterned wafer image under inspection which is obtained from the wafer image itself mixed to the layout design schemes. First a mapping between physical space and pixel space is needed. Then a template matching is a
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Chandran, Loheshwaran, Mohamed Subair Syed Akbar Ali, Abhishek Saini, Zheng Fan, and Prabhu Rajagopal. "A Study on the Influence of Wave Scattering in Metamaterial-Based Super-Resolution Imaging of Defects in Materials." In 2022 49th Annual Review of Progress in Quantitative Nondestructive Evaluation. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/qnde2022-98345.

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Abstract Recently there is much interest in metamaterial based super resolution imaging. Several demonstrations have been reported using sources or slits as targets for imaging. However, in the context of non-destructive evaluation, imaging of defects and discontinuities within a sample are of more interest. Such defects, unlike sources or slits, induce wave scattering which could potentially impact image generation. This paper studies the effects of wave scattering by subwavelength spaced defects in holey structured metamaterial based super resolution imaging using numerical (finite element)
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Nejatpour, Reza, Ali Asmari Sadabad, and Ali Akbar Akbari. "Automated Weld Defects Detection Using Image Processing and CAD Methods." In ASME 2008 International Mechanical Engineering Congress and Exposition. ASMEDC, 2008. http://dx.doi.org/10.1115/imece2008-68854.

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One of the simple, fast, and economical methods for controlling the condition of a weld is checking its superficial appearance. In this paper a method, based on the composition of Image Processing and CAD algorithms is presented for controlling different welding defects. The main purpose of this project is omission of the human interference in Visual Test of the weld. The main core of this system is a computer which analyses the captured images of a CCD camera and extracts the parameters of the weld such as size, position, surface smoothness and etc. By putting the results of analyses executed
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Szczypinski, Piotr M., Artur Klepaczko, and Marcin Kociolek. "Barley defects identification." In 2017 10th International Symposium on Image and Signal Processing and Analysis (ISPA). IEEE, 2017. http://dx.doi.org/10.1109/ispa.2017.8073598.

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Reports on the topic "Image defects"

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Nguyen, Hung. DTPH56-14-H-CAAP02 Wall Break-Through in Composite Repaired Defects. Pipeline Research Council International, Inc. (PRCI), 2017. http://dx.doi.org/10.55274/r0011839.

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Composite materials installed on pipelines where damage generated by corrosion or erosion that begins as a wall-loss defect that can transition to a through-wall defect. Critically, the damage generated by the process tends to have a region of diffuse wall loss surrounding a through-wall penetration. Design qualification of repairs for through-wall defects are performed using simulated flaws manufactured by drilling through the pipe wall. This creates straight-sided flaws with significant remaining stiffness, very different from the diffuse, tapered flaws produced by erosion or corrosion. This
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Decroux, Agnes, Kassem Kalo, and Keith Swinden. PR-393-205100-R01 IRIS X-Ray CT Qualification for Flexible Pipe Inspection (Phase 1). Pipeline Research Council International, Inc. (PRCI), 2021. http://dx.doi.org/10.55274/r0012068.

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There are several techniques available to inspect single wall carbon steel pipelines including; Magnetic flux leakage (MFL), ultrasonic testing (UT), Electro-Magnetic Acoustic Transducer (EMAT), Phased Array, guide wave testing (GWT), etc. However, for more complex structures such as flexible pipelines the technology available to inspect them is far more limited. PRCI commissioned a program (SPIM 2-1) under the Subsea TC (2017-2020) to evaluate all known and suspected technologies that could be used to provide a detailed subsea inspection of a flexible riser. PRCI produced four samples of flex
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Delwiche, Michael, Yael Edan, and Yoav Sarig. An Inspection System for Sorting Fruit with Machine Vision. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7612831.bard.

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Concepts for real-time grading of fruits and vegetables were developed, including multi-spectral imaging with structured illumination to detect and distinguish surface defects from concavities. Based on these concepts, a single-lane conveyor and inspection system were designed and evaluated. Image processing algorithms were developed to inspect and grade large quasi-spherical fruits (peaches and apples) and smaller dried fruits (dates). Adjusting defect pixel thresholds to achieve a 25% error rate on good apples, classification errors for bruise, crack, and cut classes were 51%, 42%, and 46%,
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Chen, Pictiaw, Boaz Zion, and Michael J. McCarthy. Utilization of NMR Technology for Internal Nondestructive Quality Evaluation of Fruits and Vegetables. United States Department of Agriculture, 1994. http://dx.doi.org/10.32747/1994.7568778.bard.

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Objective: The objective of this research was to investigate the potential use of NMR for evaluating various internal quality factors of fruits and vegetables, leading to the eventual development of practical techniques that are useful for future development of NMR sensors. Summary: Investigation on NMR imaging, one-dimension NMR projection, and single-pulse free-induction-decay (FID) spectrum led to the development of high-speed NMR techniques for real-time sensing of internal quality of selected fruits. NMR imaging can be used for detecting internal defects and various quality factors such a
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Nestleroth, Dr J. Bruce. PR-3-823-R01 Remote Field Eddy Current Detection of Stress-Corrosion Cracks. Pipeline Research Council International, Inc. (PRCI), 1990. http://dx.doi.org/10.55274/r0011870.

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The feasibility of detecting stress-corrosion cracks (SCC) using the Remote Field Eddy Current (RFEC) technique was demonstrated. The RFEC technique interrogates the entire thickness of the pipe and is applicable for in-line inspection. If it can be shown that the RFEC technique is effective in detecting SCC, then the technique is an ideal method for detecting the defects of interest. A defect detection model is proposed for explaining the mechanism for crack detection. For axially orientated, closed cracks, such as SCC, the conventional defect detection model proved to be too simplistic and n
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Poland, D., A. Lopez, S. Manay, and S. Sengupta. FY2006 Engineering Tech Base Report: Defect Detection in Large CT Image Sets. Office of Scientific and Technical Information (OSTI), 2006. http://dx.doi.org/10.2172/896596.

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Dawalibi. L51925 Detection of Anomalies in Coated Pipelines Using Long Range Ultrasonics. Pipeline Research Council International, Inc. (PRCI), 2002. http://dx.doi.org/10.55274/r0010644.

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Long-range guided wave pipeline inspection is claimed to be able to inspect ranges of well over 30 meters (100 Feet) in either direction (i.e. total inspection greater than 60 Meters or 200 Ft.) from a single position. In terms of inspected meters per measurement and cost per meter this technique can be a fundamental improvement from conventional methods for pipeline inspection. For inspection of hard-to-access locations it offers a good on-stream screening alternative by being able to image the pipe section from an easier-access location. Examples of inaccessible locations are road-, railway-
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Kane, Joshua James, and William Enoch Windes. Initial Assessment of X-Ray Computer Tomography image analysis for material defect microstructure. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1364233.

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Heifetz, Alexander, Xin Zhang, Jafar Saniie, and William Cleary. Detection of Defects in Additively Manufactured Metallic Materials with Machine Learning of Pulsed Thermography Images. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1673390.

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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detecti
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