Abstract
In recent years, the need for computer vision systems is increasing in various fields, such as security and visual inspection. It is crucial there to realize simple and high-speed practical vision systems. The present paper addresses the author's theoretical research and its applications developed thus far in working toward this goal. First, the problem of the conventional approach is pointed out, and the general framework of pattern recognition, in particular the feature extraction theory, is referred to as the theoretical foundation. Next, a scheme of adaptive vision system with learning capability is presented, which comprises two stages of feature extraction, namely, Higher-order Local Auto-Correlation and multivariate data analysis. Several applications are demonstrated, showing the flexible and effective performance of the proposed scheme.
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