Detecting wood surface defects with fusion algorithm of visual saliency and local threshold segmentation

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 工业控制网络与系统研究室

	Detecting wood surface defects with fusion algorithm of visual saliency and local threshold segmentation
	Wang XJ(王学娟); Wu, Shuhang ; Liu YP(刘云鹏); Wang ZP(王志平); Song Y(宋岩); Yu HB(于海斌); Ceng P(曾鹏); Wang K(王锴); Yan BJ(闫炳均); Xu AD(徐皑冬)
	2017
会议名称	9th International Conference on Graphic and Image Processing, ICGIP 2017
会议日期	October 14-16, 2017
会议地点	Qingdao, China
页码	1-9
通讯作者	Wang XJ(王学娟)
中文摘要	This paper presents a new method for wood defect detection. It can solve the over-segmentation problem existing in local threshold segmentation methods. This method effectively takes advantages of visual saliency and local threshold segmentation. Firstly, defect areas are coarsely located by using spectral residual method to calculate global visual saliency of them. Then, the threshold segmentation of maximum inter-class variance method is adopted for positioning and segmenting the wood surface defects precisely around the coarse located areas. Lastly, we use mathematical morphology to process the binary images after segmentation, which reduces the noise and small false objects. Experiments on test images of insect hole, dead knot and sound knot show that the method we proposed obtains ideal segmentation results and is superior to the existing segmentation methods based on edge detection, OSTU and threshold segmentation.
收录类别	EI ; CPCI（ISTP）
产权排序	1
会议主办者	Ocean University of China; University of Portsmouth
会议录	Proceedings of SPIE - The International Society for Optical Engineering
会议录出版者	SPIE
会议录出版地	Bellingham, WA
语种	英语
ISSN号	0277-786X
ISBN号	978-15106-1741-4
WOS记录号	WOS:000434707200067
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/22039]
专题	沈阳自动化研究所_工业控制网络与系统研究室
作者单位	1.Key Laboratory of Opto-Electronic Information Processing, Chinese Academy of Sciences, Shenyang 110016, China 2.Shenyang Institute of Automation, Chinese Academy of Sciences, China
推荐引用方式 GB/T 7714	Wang XJ,Wu, Shuhang,Liu YP,et al. Detecting wood surface defects with fusion algorithm of visual saliency and local threshold segmentation[C]. 见:9th International Conference on Graphic and Image Processing, ICGIP 2017. Qingdao, China. October 14-16, 2017.