کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
381180 1437491 2009 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Fabric defect detection based on multiple fractal features and support vector data description
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Fabric defect detection based on multiple fractal features and support vector data description
چکیده انگلیسی

Computer-vision-based automatic detection of fabric defects is one of the difficult one-class classification tasks in the real world. To overcome the incapacity of a single fractal feature in dealing with this task, multiple fractal features have been extracted in the light of the theory of and problems present in the box-counting method as well as the inherent characteristics of woven fabrics. Based on statistical learning theory, the up-to-date support vector data description (SVDD) is an excellent approach to the problem of one-class classification. A robust new scheme is presented in this paper for optimally selecting values of the parameters especially that of the scale parameter of the Gaussian kernel function involved in the training of the SVDD model. Satisfactory experimental results are finally achieved by jointly applying the extracted multiple fractal features and SVDD to the detection of defects from several datasets of fabric samples with different texture backgrounds.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Applications of Artificial Intelligence - Volume 22, Issue 2, March 2009, Pages 224–235
نویسندگان
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