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Adaptive cropping and deskewing of scanned documents based on high accuracy estimation of skew angle and cropping value

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Abstract

Scanned documents commonly suffer from skew and redundant edges when a paper document is scanned and saved as an image file. In this paper, we propose an improved algorithm that can automatically deskew and crop scanned documents. To improve the accuracy of edge detection, the image edge can be made salient based on different edge types. The estimation of the deskew and the cropping value can benefit from the salient image edge. This paper also adopts the improved region growing method to automatically obtain the cropping value to crop the scanned image. The proposed method mainly includes image preprocessing, image classification, skew angle estimation, deskewing and cropping; estimation of the cropping values is based on different image types. Compared with the previous algorithms, the proposed algorithm not only has good anti-interference ability, but can also accurately estimate the cropping value and skew angle. Since the scanned images in the database from DISEC’2013 do not have redundant edges, another experiment with redundant edges must be performed with our database. The experimental results illustrate that the proposed method performs better than other methods.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Nos. 61673129, 51674109).

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  1. College of Automation, Harbin Engineering University, Harbin, 150001, China

    Chengtao Cai, Haiyang Meng & Renjie Qiao

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  1. Chengtao Cai
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  2. Haiyang Meng
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  3. Renjie Qiao
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Correspondence to Haiyang Meng.

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Cai, C., Meng, H. & Qiao, R. Adaptive cropping and deskewing of scanned documents based on high accuracy estimation of skew angle and cropping value. Vis Comput 37, 1917–1930 (2021). https://doi.org/10.1007/s00371-020-01952-z

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