Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0167-8655(03)00057-6
Title: A nearest-neighbor chain based approach to skew estimation in document images
Authors: Lu, Y. 
Lim Tan, C. 
Keywords: Document analysis
Nearest-neighbor chain
Skew estimation
Issue Date: 2003
Citation: Lu, Y., Lim Tan, C. (2003). A nearest-neighbor chain based approach to skew estimation in document images. Pattern Recognition Letters 24 (14) : 2315-2323. ScholarBank@NUS Repository. https://doi.org/10.1016/S0167-8655(03)00057-6
Abstract: A nearest-neighbor chain (NNC) based approach is proposed in this paper to develop a skew estimation method with a high accuracy and with language-independent capability. Size restriction is introduced to the detection of nearest-neighbors (NN). Then NNCs are extracted from the adjacent NN pairs, in which the slopes of the NNCs with a largest possible number of components are computed to give the skew angle of document image. Experimental results on various types of documents containing different linguistic scripts and diverse layouts show that the proposed approach has achieved an improved accuracy for estimating document image skew angle and has an advantage of being language independent. © 2003 Elsevier B.V. All rights reserved.
Source Title: Pattern Recognition Letters
URI: http://scholarbank.nus.edu.sg/handle/10635/39742
ISSN: 01678655
DOI: 10.1016/S0167-8655(03)00057-6
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