An Optimization Methodology for Document Structure Extraction on Latin Character Documents
IEEE Transactions on Pattern Analysis and Machine Intelligence
A nearest-neighbor chain based approach to skew estimation in document images
Pattern Recognition Letters
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This paper describes an algorithm to estimate the text skew angle in a document image. The algorithm utilizes the recursive morphological transforms and yields accurate estimates of text skew angles on a large document image data set. The algorithm computes the optimal parameter settings on the fly without any human interaction. In this automatic mode, experimental results indicate that the algorithm generates estimated text skew angles within 0.5/spl deg/ of the true text skew angles with a probability of 99%. To process a 300 dpi document image, the algorithm takes 10 seconds on SUN Sparc 10 machines.