A new curve detection method: randomized Hough transform (RHT)
Pattern Recognition Letters
Randomized Hough transform (RHT): basic mechanisms, algorithms, and computational complexities
CVGIP: Image Understanding
Dimension reduction by local principal component analysis
Neural Computation
Mixtures of probabilistic principal component analyzers
Neural Computation
Binary digital image processing: a discrete approach
Binary digital image processing: a discrete approach
Image categorization via robust pLSA
Pattern Recognition Letters
Energy based competitive learning
Neurocomputing
Robust line detection using two-orthogonal direction image scanning
Computer Vision and Image Understanding
A novel Hough transform method for line detection by enhancing accumulator array
Pattern Recognition Letters
A fixed-point EM algorithm for straight line detection
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
A gradient BYY harmony learning algorithm on mixture of experts for curve detection
IDEAL'05 Proceedings of the 6th international conference on Intelligent Data Engineering and Automated Learning
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We solve the tasks of strip line detection and thinning in image processing and pattern recognition with the help of a statistical learning technique called rival penalized competitive learning based local principal component analysis. Due to its model selection and noise resistance ability, the technique is experimentally shown to outperform conventional Hough transform and thinning algorithms.