A nearest-neighbor chain based approach to skew estimation in document images
Pattern Recognition Letters
Improved Nearest Neighbor Based Approach to Accurate Document Skew Estimation
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Skew detection using wavelet decomposition and projection profile analysis
Pattern Recognition Letters
e-PCP: A robust skew detection method for scanned document images
Pattern Recognition
Movement invariants-based algorithm for medical image tilt correction
International Journal of Automation and Computing
Document image analysis: issues, comparison of methods and remaining problems
Artificial Intelligence Review
A new approach for instance-based skew estimation
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part IV
Hi-index | 0.00 |
This paper describes an algorithm to estimate the skew angle of document images. It utilizes the nearest-neighbor clustering paradigm. In contrast to earlier approaches, the local clustering process is focused to a subset of plausible neighbors.The proposed skew detection algorithm is potentially useful to any feature points that reveal the dominant orientation of document images in their entirety. Experimental results using connected components and pass codes as features are presented to show the general usefulness of the proposed algorithm.