Proceedings PaperCombining sensor information from automated visual inspection for quickest detection of disorders
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This paper is concerned with automated visual inspection of manufactured products which is carried out by means of pixel-by-pixel comparison of the sensed image of the product to be inspected with some reference pattern (or image). In this framework, the disorder detection problem (or the change-point problem) is of basic importance which consists in detecting possible abrupt changes in parameters of the initial distribution of observations of a process occurring at unknown time points. In this paper, the problem is considered from the point of view of both the parametric and non-parametric approaches. The purpose of this paper is to give a presentation of several sequential jump detection algorithms which combine sensor information from automated visual inspection and also have applications in such areas as remote sensing, target recognition, environmental monitoring, etc. In order to illustrate these algorithms, the examples are given.