Texture defects detection on microscale images of materials
Автор: Plasitnin Anatoliy Igorevich, Khramov Alexander Grigorievich, Soifer Victor Alexandrovich
Журнал: Компьютерная оптика @computer-optics
Рубрика: Наномасштабные изображения
Статья в выпуске: 2 т.35, 2011 года.
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The article presents a method for texture defect detection based on image neighborhoods set analysis. Method allows estimating decision function based on images with defects, as well as on images without defects. We provide steel microstructure defects detection results that show the advantages of described method.
Texture images, markov random fields, single-class svm, kernel function, non-linear separation boundary
Короткий адрес: https://sciup.org/14058999
IDR: 14058999
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