A novel image segmentation approach for wood plate surface defect classification through convex optimization

Verfasser / Beitragende:
Chang, Zhanyuan; Zhang, Yizhuo; Cao, Jun
Ort, Verlag, Jahr:
Heidelberg : Springer, 11-01-2018
Springer Nature B.V,
College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, People's Republic of China,
College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, People's Republic of China%College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, People's Republic of China,
Zeitschriftentitel:
Journal of forestry research, Jg. 29; H. 6; S. 1789 - 1795
Format:
Journal Article
Online Zugang:
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ID: FETCH-LOGICAL-c2472-31340edb24295f844ce3cd8e6506a322e3a73baab7e35224265053764506bd6f3

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Journal of forestry research

Electrical engineering; Equipment and supplies; Image processing; Electric properties; Classifiers; Target recognition; Segmentation; Wood; Surface defects; Adaptability; Regression analysis; Optimization; Weight; Image detection; Pinholes; Image segmentation; Plates (structural members); Classification; Feature extraction; Convexity; Pretreatment; Convex analysis; Image classification; Structure similarity; Defect recognition; Convex optimization; Decision tree; Threshold segmentation

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