NDLI: Non-destructive crack detection of preserved eggs using a machine vision and multivariate analysis

Content Provider	Springer Nature Link
Author	Wang, Fang Zhang, Shu Tan, Zuojun
Copyright Year	2017
Abstract	Pidan or century egg, also known as preserved egg, is one of the most traditional and popular egg products in China. The crack detection of preserved eggshell is very important to guarantee its quality. In this study, we develop an image algorithm for preserved eggshell’s crack detection by using natural light and polarized image. Four features including crack length, crack state coefficient, maximum projection and angular point are extracted from the natural light image by morphology calculus algorithms. The support vector machines (SVM) model with radial basis kernel function is established using the four features with an accuracy of about 92%. The detection accuracy is improved to 94% by using a new characteristic parameter of crack length on polarization image. The Multi-information fusion analysis indicates the potential for cracks detection by a real-time synthesis imaging system.
Starting Page	257
Ending Page	262
Page Count	6
File Format	PDF
ISSN	10071202
Journal	Wuhan University Journal of Natural Sciences
Volume Number	22
Issue Number	3
e-ISSN	19934998
Language	English
Publisher	Wuhan University
Publisher Date	2017-05-06
Publisher Place	Wuhan
Access Restriction	Subscribed
Subject Keyword	preserved egg crack morphology calculus algorithms polarized light support vector machines (SVM) model Life Sciences Materials Science Computer Science
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

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