Functional Pattern Recognition of 3D Laser Scanned Images of Wood-Pulp Chips
We evaluate the appropriateness of applying a functional rather than the typical vectorial approach to a pattern recognition problem. The problem to be resolved was to construct an online system for controlling wood-pulp chip granulometry quality for implementation in a wood-pulp factory. A functional linear model and a functional logistic model were used to classify the hourly empirical distributions of wood-chip thicknesses estimated on the basis of images produced by a 3D laser scanner. The results obtained using these functional techniques were compared to the results of their vectorial counterparts and support vector machines, whose input consisted of several statistics of the hourly empirical distribution. We conclude that the empirical distributions have sufficiently rich functional traits so as to permit the pattern recognition process to benefit from the functional representation.
KeywordsSupport Vector Machine Wood Chip Vectorial Model Quality Control System Pattern Recognition Problem
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- 1.Broderick, G., Cacchione, E., Héroux, Y.: The importance of distribution statistics in the characterization of chip quality. Tappi Journal 81(2), 131–142 (1998)Google Scholar
- 6.SCAN-47:92: Wood chips for pulp production - thickness and thickness distribution. Scandinavian Pulp, Paper and Board Testing Committee. Stockholm, Sweden (1992)Google Scholar
- 7.Scholkopf, B., Smola, A.J.: Learning with Kernels. MIT Press, Cambridge (2002)Google Scholar