Estimation and monitoring of product aesthetics: application to manufacturing of "engineered stone" countertops
A new machine vision approach for quantitatively estimating and monitoring the appearance and aesthetics of manufactured products is presented. The approach is composed of three steps: (1) wavelet-based textural feature extraction from product images, (2) estimation of measures of the product appearance through subspace projection of the textural features, and (3) monitoring of the appearance in the latent variable subspace of the textural features. The methodology is specifically designed to treat the stochastic nature of the visual appearance of many manufactured products. This nondeterministic aspect of product appearance has been an obstacle for the success of machine vision in many industries. The emphasis of this approach is on the consistent and quantitative estimation of continuous variations in visual appearance rather than on classification into discrete classes. This allows for the on-line monitoring and the eventual feedback control of product appearance. This approach is successfully applied to the estimation and monitoring of the aesthetic quality of manufactured stone countertops.
monitoring machine vision visual appearance engineered stone countertops wavelet texture analysis principal component analysis