Weighted Parzen Windows for Pattern Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fourier-Based Object Description in Defect Image Retrieval
Machine Vision and Applications
Data Mining
Visual inspection of machined metallic high-precision surfaces
EURASIP Journal on Applied Signal Processing
Journal on Image and Video Processing - Regular
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Nonlinear kernel-based statistical pattern analysis
IEEE Transactions on Neural Networks
Generalized neural trees for pattern classification
IEEE Transactions on Neural Networks
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A general free-form surface inspection approach relying on the projection of a structured light pattern and the interpretation of the generated stripe structures by means of Fourier-based features is proposed in this paper. The major concerns of this paper are the determination of various refrence sets of stripe patterns, and the detailed investigation on the subset of Fourier features that best characterizes free-form bright/dark structures. In order to tackle the inspection problem with a general approach, a first part of this paper is dedicated to the definition of different image data sets that correspond to various types of free-form specular shapes recorded with a structured illumination. A second part deals with the optimization of the most appropriate pattern recognition process. The optimization is dedicated to the use of different pattern arrangements, and the evaluation of different Fourier feature subsets. It is shown that with only 10 Fourier features and a certain pattern arrangement, high classification rates of free-form surfaces can be obtained.