Matlab based automated surface defect detection system for ceremic tiles using image processing

2017 ◽  
Author(s):  
Yasantha C. Samarawickrama ◽  
Chamira D. Wickramasinghe
Keyword(s):  
Image Processing ◽  
Defect Detection ◽  
Surface Defect ◽  
Detection System ◽  
Surface Defect Detection

scholarly journals Research on Surface Defect Detection of Aluminum based on Image Processing

2020 ◽  
Vol 25 ◽  
pp. 822-825
Author(s):  
Xuemin Liu ◽  
Ce Bian ◽  
Di Yin ◽  
Yuxuan Zhu ◽  
Yasheng Yuan ◽  
...  
Keyword(s):  
Image Processing ◽  
Defect Detection ◽  
Surface Defect ◽  
Surface Defect Detection

Research on Key Technology of Cold-Rolled Aluminum Plate Surface Defect Detection System

2013 ◽  
Vol 433-435 ◽  
pp. 915-918 ◽  
Author(s):  
Hai Lun Zhang ◽  
Xing Guang Qi ◽  
Xiao Ting Li
Keyword(s):  
Defect Detection ◽  
Surface Defect ◽  
Detection System ◽  
Aluminum Plate ◽  
Aluminum Surface ◽  
Image Processing Algorithm ◽  
Key Technologies ◽  
Rolled Aluminum ◽  
Surface Defect Detection ◽  
Cold Rolled

This paper presents the research of several key technologies during the implementation of cold-rolling aluminum surface defect detection system, including the difficulty of achieving these key technologies and the improvement of image processing algorithm. Through the installation and commissioning on actual production line, summarize and analyze the requirements of the hardware and software design for highly reflective aluminum plate, to achieve the control of product quality at present.

A Review Paper on Product Surface Defect Detection of Ironing Process

2016 ◽  
Vol 836 ◽  
pp. 147-152
Author(s):  
Akhmad Faizin ◽  
Arif Wahjudi ◽  
I. Made Londen Batan ◽  
Agus Sigit Pramono
Keyword(s):  
Image Processing ◽  
Surface Roughness ◽  
Defect Detection ◽  
Surface Defect ◽  
Surface Defects ◽  
Forming Process ◽  
Metal Forming Process ◽  
Surface Defect Detection ◽  
Product Surface ◽  
Processing Techniques

The quality of product of manufacturing industries depends on dimension accurately and surface roughness quality. There are many types of surface defects and levels of surface roughness quality. Ironing process is one type of metal forming process, which aims to reduce the wall thickness of the cup-shaped or pipes products, thus increasing the height of the wall. Manually surface inspection procedures are very inadequate to ensure the surface in guaranteed quality. To ensure strict requirements of customers, the surface defect inspection based on image processing techniques has been found to be very effective and popular over the last two decades. The paper has been reviewed some papers based on image processing for defect detection. It has been tried to find some alternatives of useful methods for product surface defect detection of ironing process.

The PCB Surface Defect Detection System Based on GPU Acceleration

2015 ◽  
Vol 713-715 ◽  
pp. 347-352
Author(s):  
Yu Liu ◽  
Si Zhe Li
Keyword(s):  
Defect Detection ◽  
Rapid Detection ◽  
Surface Defect ◽  
Printed Circuit Board ◽  
Detection System ◽  
Processing System ◽  
Circuit Board ◽  
Computing Platform ◽  
Surface Defect Detection ◽  
Time Requirements

Defective products are unavoidable in printed circuit board production process, so rapid detection and identificationmethods are badly in need of. PCB surface defect detection including a series of processing such as surface imagecapture, mixed noise filtering,images registering and so on, so it takes a lot of CPU time. To improve detection speed, based on GPU parallel computing platform, we designed a reasonable parallel processing system for PCB defect detectionto meet the need of real-time requirements of a production line. Experimental results show that parallel image processing algorithms based on GPU can achieve good results compared to the CPU-based serial algorithm (with speed up ratio up to8.34 in this paper),providing a new approachfor rapid detection of PCB surface defect.

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