Min Zhang^*, Haixu Xi

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3911-3923, 2023, DOI:10.32604/csse.2023.036709 - 03 April 2023

Abstract For Printed Circuit Board (PCB) surface defect detection, traditional detection methods mostly focus on template matching-based reference method and manual detections, which have the disadvantages of low defect detection efficiency, large errors in defect identification and localization, and low versatility of detection methods. In order to further meet the requirements of high detection accuracy, real-time and interactivity required by the PCB industry in actual production life. In the current work, we improve the You-only-look-once (YOLOv4) defect detection method to train and detect six types of PCB small target defects. Firstly, the original Cross Stage Partial… More >

Siddiqui Muhammad Yasir¹, Hyunsik Ahn^2,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1847-1861, 2023, DOI:10.32604/cmc.2023.035698 - 06 February 2023

Abstract Deep learning has been constantly improving in recent years, and a significant number of researchers have devoted themselves to the research of defect detection algorithms. Detection and recognition of small and complex targets is still a problem that needs to be solved. The authors of this research would like to present an improved defect detection model for detecting small and complex defect targets in steel surfaces. During steel strip production, mechanical forces and environmental factors cause surface defects of the steel strip. Therefore, the detection of such defects is key to the production of high-quality… More >

Fengyu Xu^1,2, Masoud Kalantari³, Bangjian Li², Xingsong Wang^2,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2209-2226, 2023, DOI:10.32604/cmc.2023.027102 - 06 February 2023

Abstract The automatically defect detection method using vision inspection is a promising direction. In this paper, an efficient defect detection method for detecting surface damage to cables on a cable-stayed bridge automatically is developed. A mechanism design method for the protective layer of cables of a bridge based on vision inspection and diameter measurement is proposed by combining computer vision and diameter measurement techniques. A detection system for the surface damages of cables is de-signed. Images of cable surfaces are then enhanced and subjected to threshold segmentation by utilizing the improved local grey contrast enhancement method More >

Qunbiao Wu¹, Zhen Wang^1,*, Haifeng Fang¹, Junji Chen¹, Xinfeng Wan²

Computer Systems Science and Engineering, Vol.46, No.1, pp. 961-979, 2023, DOI:10.32604/csse.2023.036239 - 20 January 2023

Abstract For surface defects in electronic water pump shells, the manual detection efficiency is low, prone to misdetection and leak detection, and encounters problems, such as uncertainty. To improve the speed and accuracy of surface defect detection, a lightweight detection method based on an improved YOLOv5s method is proposed to replace the traditional manual detection methods. In this method, the MobileNetV3 module replaces the backbone network of YOLOv5s, depth-separable convolution is introduced, the parameters and calculations are reduced, and CIoU_Loss is used as the loss function of the boundary box regression to improve its detection accuracy.… More >

Nadeem Jabbar Chaudhry^1,*, M. Bilal Khan², M. Javaid Iqbal¹, Siddiqui Muhammad Yasir³

Journal on Artificial Intelligence, Vol.4, No.4, pp. 245-259, 2022, DOI:10.32604/jai.2022.038875 - 25 May 2023

Abstract Recently, outstanding identification rates in image classification tasks were achieved by convolutional neural networks (CNNs). to use such skills, selective CNNs trained on a dataset of well-known images of metal surface defects captured with an RGB camera. Defects must be detected early to take timely corrective action due to production concerns. For image classification up till now, a model-based method has been utilized, which indicated the predicted reflection characteristics of surface defects in comparison to flaw-free surfaces. The problem of detecting steel surface defects has grown in importance as a result of the vast range… More >

Xin Zihao¹, Wang Hongyuan^1,*, Qi Pengyu¹, Du Weidong², Zhang Ji¹, Chen Fuhua³

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5925-5938, 2022, DOI:10.32604/cmc.2022.026943 - 21 April 2022

Abstract For a long time, the detection and extraction of printed surface defects has been a hot issue in the print industry. Nowadays, defect detection of a large number of products still relies on traditional image processing algorithms such as scale invariant feature transform (SIFT) and oriented fast and rotated brief (ORB), and researchers need to design algorithms for specific products. At present, a large number of defect detection algorithms based on object detection have been applied but need lots of labeling samples with defects. Besides, there are many kinds of defects in printed surface, so… More >

Adriano G. Passos, Tiago Cousseau, Marco A. Luersen^*

Computer Systems Science and Engineering, Vol.41, No.2, pp. 583-593, 2022, DOI:10.32604/csse.2022.020020 - 25 October 2021

Abstract A proper detection and classification of defects in steel sheets in real time have become a requirement for manufacturing these products, largely used in many industrial sectors. However, computers used in the production line of small to medium size companies, in general, lack performance to attend real-time inspection with high processing demands. In this paper, a smart deep convolutional neural network for using in real-time surface inspection of steel rolling sheets is proposed. The architecture is based on the state-of-the-art SqueezeNet approach, which was originally developed for usage with autonomous vehicles. The main features of More >

Yu-Cheng Chou¹, Wei-Chieh Liao², Yan-Liang Chen², Ming Chang², Po Ting Lin³

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 79-90, 2019, DOI:10.31209/2018.100000011

Abstract This paper presents the Distributed Heterogeneous Inspection System (DHIS), which comprises two CUDA workstations and is equipped with CPU distributed computing, CPU concurrent computing, and GPU concurrent computing functions. Thirty-two grayscale images, each with 5,000× 12,288 pixels and simulated defect patterns, were created to evaluate the performances of three system configurations: (1) DHIS; (2) two CUDA workstations with CPU distributed computing and GPU concurrent computing; (3) one CUDA workstation with GPU concurrent computing. Experimental results indicated that: (1) only DHIS can satisfy the time limit, and the average turnaround time of DHIS is 37.65% of More >

M. Chang^1,2,3, Y. C. Chou^1,2, P. T. Lin^1,2, J. L. Gabayno^2,4

CMC-Computers, Materials & Continua, Vol.42, No.2, pp. 125-140, 2014, DOI:10.3970/cmc.2014.042.125

Abstract Automated optical inspection systems installed in production lines help ensure high throughput by speeding up inspection of defects that are otherwise difficult to detect using the naked eye. However, depending on the size and surface properties of the products such as micro-cracks on touchscreen panels glass cover, the detection speed and accuracy are limited by the imaging module and lighting technique. Therefore the current inspection methods are still delegated to a few qualified personnel whose limited capacity has been a huge tradeoff for high volume production. In this study, an automated optical technology for in-line… More >

B. Yang², V. K. Tewary³

CMES-Computer Modeling in Engineering & Sciences, Vol.15, No.3, pp. 165-178, 2006, DOI:10.3970/cmes.2006.015.165

Abstract Green's function (GF) modeling of defects may take effect only if the GF as well as its various integrals over a line, a surface and/or a volume can be efficiently evaluated. The GF is needed in modeling a point defect, while integrals are needed in modeling line, surface and volumetric defects. In a matrix of multilayered, generally anisotropic and linearly elastic and piezoelectric materials, the GF has been derived by applying 2D Fourier transforms and the Stroh formalism. Its use involves another two dimensions of integration in the Fourier inverse transform. A semi-analytical scheme has… More >