학술논문

Grinding mode classification of ground ceramics using 2-dimensional wavelet transform
Document Type
Conference
Source
Proceedings 1996 IEEE Conference on Emerging Technologies and Factory Automation. ETFA '96 Emerging technologies and factory automation Emerging Technologies and Factory Automation, 1996. EFTA '96. Proceedings., 1996 IEEE Conference on. 1:70-75 vol.1 1996
Subject
Computing and Processing
Communication, Networking and Broadcast Technologies
Power, Energy and Industry Applications
Ceramics
Discrete wavelet transforms
Surface waves
Surface topography
Image processing
Pattern recognition
Feature extraction
Frequency
Humans
Inspection
Language
Abstract
A new method for characterizing surface topography using a 2-dimensional discrete wavelet transform (2-D DWT) has been developed. The wavelet transform (WT) is the basis for a wide range of techniques applied in image processing and pattern recognition. Its main advantages over other feature extraction methods are the space-frequency localization, and the multi-resolution view of the frequency components of a signal. In this paper, an automatic grinding modes classification technique using a 2-D DWT is introduced, and comparisons of automatic grinding modes classification and human eye inspection are also examined.