Abstract
Document images can have numerous noises that should be filtered to eliminate those unutilized objects. Skewness is liable not to understand the texts clearly in the document image. A morphological technique is being conducted to preprocess the image. Connected component analysis along with the bounding box approach is introduced to figure out a line. A number of longest connected components are extracted from numerous illustrations. In order to detect a precise skewed angle, the least square method is applied to the logically selected regions to acquire the best fitting line. The skewed angle is discovered by averaging angles of best-fitting lines. The proposed system is already applied on the printed document image and got tremendous accuracy during execution.
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Imran, F., Ali Hossain, M., Al Mamun, M., Singh, B.K., Choudhury, T. (2021). Global Skew Detection and Correction of Document Image Based on Least Square Method and Extensive Connected Component Analysis. In: Singh, J., Kumar, S., Choudhury, U. (eds) Innovations in Cyber Physical Systems. Lecture Notes in Electrical Engineering, vol 788. Springer, Singapore. https://doi.org/10.1007/978-981-16-4149-7_38
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DOI: https://doi.org/10.1007/978-981-16-4149-7_38
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