کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10361308 | 870182 | 2005 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Invariant and adaptive geometrical texture features for defect detection and classification
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
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چکیده انگلیسی
Automatic texture defect detection is highly important for many fields of visual inspection. We introduce novel, geometrical texture features for this task, which are Euclidean motion invariant and texture adaptive: An algebraic function (rational, Padé, or polynomial) is integrated over intensities in local, circular neighborhoods on the image including an anisotropical texture analysis. Adaptiveness is achieved through the optimization of this feature kernel and further coefficients based on a simplex energy minimization, constrained by a measure of texture discrimination (Fisher criterion). A backpropagation trained, multilayer perceptron network classifies the textures locally. Our approach contains new properties, usually not common in feature theories: Theoretically implicit, multiple invariances and an automatic and specific adaptation of the features to the texture images. Experiments with a fabric data set and Brodatz textures reveal up to 98.6% recognition accuracy.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 38, Issue 10, October 2005, Pages 1546-1559
Journal: Pattern Recognition - Volume 38, Issue 10, October 2005, Pages 1546-1559
نویسندگان
D.R. Rohrmus,