Local PCA for Strip Line Detection and Thinning

We solve the tasks of strip line detection and thinning in image processing and pattern recognition in help of an energy minimization technique called rival penalized competitive learning (RPCL) based local principal component analysis (PCA). Due to its model selection and noise resistance ability, the technique is shown to outperform conventional Hough transform and thinning algorithms via a number of simulations.

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