BIOMEDICAL IMAGING GROUP (BIG)
Laboratoire d'imagerie biomédicale (LIB)

Feature Extraction and Decision Procedure for Automated Inspection of Textured Materials

M. Unser, F. Ade

Pattern Recognition Letters, vol. 2, no. 3, pp. 185–191, March 1984.

This paper proposes a general system approach applicable to the automatic inspection of textured material. First, the input image is preprocessed in order to be independent of acquisition non-uniformities. A tone-to-texture transform is then performed by mapping the original grey level picture on a multivariate local feature sequence, which turns out to be normally distributed. More specifically, features derived with the help of the Karhunen-Loève decomposition of a small neighbourhood of each pixel are used. A decision as to conformity with a reference texture is arrived at by thresholding the Mahalanobis distance for every realization of the feature vector. It is shown that this approach is optimum under the Gaussian assumption in the sense that it has a minimum acceptance region for a fixed probability of false rejection. 

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AUTHOR="Unser, M. and Ade, F.",
TITLE="Feature Extraction and Decision Procedure for Automated
	Inspection of Textured Materials",
JOURNAL="Pattern Recognition Letters",
YEAR="1984",
volume="2",
number="3",
pages="185--191",
month="March",
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