scholarly journals Real-time portable system for fabric defect detection using an ARM processor

2012 ◽  
Author(s):  
J. A. Fernandez-Gallego ◽  
J. P. Yañez-Puentes ◽  
B. Ortiz-Jaramillo ◽  
J. Alvarez ◽  
S. A. Orjuela-Vargas ◽  
...  
Keyword(s):  
Real Time ◽  
Defect Detection ◽  
Arm Processor ◽  
Fabric Defect Detection ◽  
Fabric Defect ◽  
Portable System

Fast and Parallel Summed Area Table for Fabric Defect Detection

2016 ◽  
Vol 30 (09) ◽  
pp. 1660004 ◽  
Author(s):  
Khaled Ragab
Keyword(s):  
Real Time ◽  
Defect Detection ◽  
Gpu Computing ◽  
Processing Unit ◽  
Detection Algorithms ◽  
Fabric Defect Detection ◽  
Fabric Defect ◽  
Time Requirements ◽  
Robustness To Noise ◽  
Graphical Processing

Automating fabric defect detection has a significant role in fabric industries. However, the existing fabric defect detection algorithms lack the real-time performance that is required in real applications due to their high demanding computation. To ensure real time, high accuracy and reliable fabric defect detection this paper developed a fast and parallel normalized cross-correlation algorithm based on summed-area table technique called PFDD-SAT. To meet real-time requirements, extensive use of the NVIDIA CUDA framework for Graphical Processing Unit (GPU) computing is made. The detailed implementation steps of the PFDD-SAT are illustrated in this paper. Several experiments have been carried out to evaluate the detection time and accuracy and then the robustness to illumination and Gaussian noises. The results show that the PFDD-SAT has robustness to noise and speeds the defect detection process more than 200 times than normal required time and that greatly met the needs for real-time automatic fabric defect detection.

scholarly journals Real-Time Fabric Defect Detection Using Accelerated Small-Scale Over-Completed Dictionary of Sparse Coding

10.5772/62058 ◽  
2016 ◽  
Vol 13 (1) ◽  
pp. 1 ◽  
Author(s):  
Tianpeng Feng ◽  
Lian Zou ◽  
Jia Yan ◽  
Wenxuan Shi ◽  
Yifeng Liu ◽  
...  
Keyword(s):  
Real Time ◽  
Defect Detection ◽  
Sparse Coding ◽  
Small Scale ◽  
Fabric Defect Detection ◽  
Fabric Defect

Intelligent Real-Time Fabric Defect Detection

2007 ◽  
pp. 1297-1307 ◽  
Author(s):  
Hugo Peres Castilho ◽  
Paulo Jorge Sequeira Gonçalves ◽  
João Rogério Caldas Pinto ◽  
António Limas Serafim
Keyword(s):  
Real Time ◽  
Defect Detection ◽  
Fabric Defect Detection ◽  
Fabric Defect

Real-time Fabric Defect Detection Algorithm Based on S-YOLOV3 Model

2020 ◽  
Vol 57 (16) ◽  
pp. 161001
Author(s):  
周君 Zhou Jun ◽  
景军锋 Jing Junfeng ◽  
张缓缓 Zhang Huanhuan ◽  
王震 Wang Zhen ◽  
黄汉林 Huang Hanlin
Keyword(s):  
Real Time ◽  
Defect Detection ◽  
Detection Algorithm ◽  
Fabric Defect Detection ◽  
Fabric Defect

scholarly journals Fabric Defect Detection based on Improved Object as Point

2021 ◽  
Vol 13 (3) ◽  
pp. 1-13
Author(s):  
Yuan He ◽  
Xin-Yue Huang ◽  
Francis Eng Hock Tay
Keyword(s):  
Real Time ◽  
Defect Detection ◽  
Detection Method ◽  
Detection Algorithm ◽  
Error Rates ◽  
Automated Detection ◽  
Fabric Defect Detection ◽  
Fabric Defect ◽  
Low Efficiency

In the field of fabric manufacturing, many factories still utilise the traditional manual detection method. It requires a lot of labour, resulting in high error rates and low efficiency. In this paper, we represent a realtime automated detection method based on object as point. This work makes three attributions. First, we build a fabric defects database and augment the data to training the intelligence model. Second, we provide a real-time fabric defects detection algorithm, which have potential to be applied in manufacturing. Third, we figure out CenterNet with soft NMS will improved the performance in fabric defect detection area, which is considered an NMS-free algorithm. Experiment results indicated that our lightweight network based method can effectively and efficiently detect five different fabric defects.

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