Your Search Results

Use this resource - and many more! - in your textbook!

AcademicPub holds over eight million pieces of educational content for you to mix-and-match your way.

Experience the freedom of customizing your course pack with AcademicPub!
Not an educator but still interested in using this content? No problem! Visit our provider's page to contact the publisher and get permission directly.

Feature extraction algorithm based on adaptive wavelet packet for surface defect classification

By: Choi, J.Y.; Choi, C.-H.; Lee, C.S.; Choi, S.H.; Kim, Y.K.;

1996 / IEEE / 0-7803-3259-8

Description

This item was taken from the IEEE Periodical ' Feature extraction algorithm based on adaptive wavelet packet for surface defect classification ' This paper proposes a feature extraction method to effectively handle the textural characteristics in images with defects in cold rolled strips. An adaptive wavelet packet scheme is developed to produce the optimum number of features automatically through subband coding gain. Also four classical entropy features in the images with defects are used as local features in the spatial domain. A neural network is used to classify the defects from these features. Experiments with real image data show good training and generalization performances of the proposed method.