Method and algorithms for cascade classification of sulfur print images of billet transverse templates

I. A. Posokhov ; O. S. Logunova ; A. Yu. Mikov

Journal of computational and engineering mathematics, Tome 3 (2016) no. 4, pp. 11-40

Résumé

This paper presents studies of sulfur print images of continuous cast billet transverse templates. The authors determined a problem of low reliability of information about the quality of billets. When assessing an image visually, such assessment is subjective with a human factor to a large extent. The authors developed a control point layout chart to collect graphical information in the course of casting billets. It is proposed to introduce three classes of images broken up by a template brightness/foreground ratio. Regarding an increased complexity of algorithms, the authors proposed the cascade classification of images. The technique includes assessment of images by shape-generating parameters of a histogram, by a distance to reference normed histograms, and by applying fuzzy logic methods. Experimental performance of the cascade technique showed that a simplified technique by assessing shape-generating parameters had expressly identified $22\%$ of all images, by assessing a distance to reference normed histograms – $70\%$ of the rest, and only by applying fuzzy logic methods all the rest images had been unambiguously identified. A $100\%$ success of the classification is achieved only when applying all cascades of the developed technique.

Détail

Keywords: sulfur print images, image histogram, shape-generating parameters, distance between objects, object identification rules, cascade classification.