CASIA OpenIR  > 模式识别国家重点实验室  > 机器人视觉
Surface defect saliency of magnetic tile
Yibin Huang1; Congying qiu; Kui yuan1
发表期刊The visual computer
ISSN1432-2315
2018-08
卷号34期号:8页码:1-12
摘要

Computer vision builds a connection between image processing and industrials, bringing modern perception to the automated  manufacture of magnetic tiles. In this article, we propose a real-time model called MCuePush U-Net, specifically designed for saliency detection of surface defect. Our model consists of three main components: MCue, U-Net and Push network. MCue generates three-channel resized inputs, including one MCue saliency image and two raw images; U-Net learns the most informative regions, and essentially it is a deep hierarchical structured convolutional network; Push network defines the specific location of predicted surface defects with bounding boxes, constructed by two fully connected layers and one output layer. We show that the model exceeds the state of the art in saliency detection of magnetic tiles, in which it both effectively and explicitly maps multiple surface defects from low-contrast images. The proposed model significantly reduces time cost  of machinery from 0.5s per image to 0.07s and enhances detection accuracy for image-based defect examinations.

关键词Saliency Surface Defect Inspection
收录类别SCI
语种英语
WOS记录号WOS:000511966800008
引用统计
被引频次:166[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/23367
专题模式识别国家重点实验室_机器人视觉
通讯作者Yibin Huang
作者单位1.中国科学院自动化研究所
2.哥伦比亚大学
第一作者单位中国科学院自动化研究所
通讯作者单位中国科学院自动化研究所
推荐引用方式
GB/T 7714
Yibin Huang,Congying qiu,Kui yuan. Surface defect saliency of magnetic tile[J]. The visual computer,2018,34(8):1-12.
APA Yibin Huang,Congying qiu,&Kui yuan.(2018).Surface defect saliency of magnetic tile.The visual computer,34(8),1-12.
MLA Yibin Huang,et al."Surface defect saliency of magnetic tile".The visual computer 34.8(2018):1-12.
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