In recent years, the need for computer vision systems is increasing in various fields, such as security monitoring and visual inspection. It is crucial to realize simple and high-speed vision systems especially for practical usage. This paper addresses the author's theoretical research and its applications developed thus far in working toward this goal. First, the problems of the conventional approach are pointed out, and the general framework of pattern recognition, in particular the feature extraction theory, is explained as the theoretical foundation of the present research. Then 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.
View full abstract