The Copper Surface Defects Inspection System Based on Computer Vision

2008 ◽  
Author(s):  
Ping Wang ◽  
Xuewu Zhang ◽  
Yan Mu ◽  
Zhihui Wang
Keyword(s):  
Computer Vision ◽  
Surface Defects ◽  
Copper Surface ◽  
Inspection System ◽  
Defects Inspection

scholarly journals A Combined Image Inspection System with Discrimination of Various Kinds of Surface Defects

1995 ◽  
Vol 115 (3) ◽  
pp. 452-459
Author(s):  
Saburo Okada ◽  
Masaaki Imade ◽  
Hidekazu Miyauchi ◽  
Tetsuhiro Sumimoto ◽  
Hideki Yamamoto
Keyword(s):  
Surface Defects ◽  
Inspection System ◽  
Image Inspection

Detection and classification of surface defects of gun barrels using computer vision and machine learning

Measurement ◽  
2015 ◽  
Vol 60 ◽  
pp. 222-230 ◽  
Author(s):  
Rajalingappaa Shanmugamani ◽  
Mohammad Sadique ◽  
B. Ramamoorthy
Keyword(s):  
Machine Learning ◽  
Computer Vision ◽  
Surface Defects

Computer Vision Based Technique for Surface Defect Detection of Apples

2014 ◽  
pp. 111-121
Author(s):  
C. J. Prabhakar ◽  
S. H. Mohana
Keyword(s):  
Computer Vision ◽  
Defect Detection ◽  
Surface Defects ◽  
Quality Standards ◽  
Production Costs ◽  
Automatic Inspection ◽  
Segmentation Technique ◽  
Surface Defect Detection ◽  
Fruit Grading

The automatic inspection of quality in fruits is becoming of paramount importance in order to decrease production costs and increase quality standards. Computer vision techniques are used in fruit industry for fruit grading, sorting, and defect detection. In this chapter, we review recent approaches for automatic inspection of quality in fruits using computer vision techniques. Particularly, we focus on the review of advances in computer vision techniques for automatic inspection of quality of apples based on surface defects. Finally, we present our approach to estimate the defects on the surface of an apple using grow-cut and multi-threshold based segmentation technique. The experimental results show that our method effectively estimates the defects on the surface of apples significantly more effectively than color based segmentation technique.

Pipe morphology defects inspection system with active stereo omnidirectional vision sensor

2016 ◽  
Vol 45 (11) ◽  
pp. 1117005
Author(s):  
汤一平 Tang Yiping ◽  
鲁少辉 Lu Shaohui ◽  
吴 挺 Wu Ting ◽  
韩国栋 Han Guodong
Keyword(s):  
Inspection System ◽  
Omnidirectional Vision ◽  
Vision Sensor ◽  
Defects Inspection ◽  
Active Stereo
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