Exposure Bracketing Techniques for Camera Document Image Enhancement
Source abstract
Abstract
Capturing document images using digital cameras in uneven lighting conditions is challenging, leading to poorly captured images, which hinders the processing that follows, such as Optical Character Recognition (OCR). In this paper, we propose the use of exposure bracketing techniques to solve this problem. Instead of capturing one image, we used several images that were captured with different exposure settings and used the exposure bracketing technique to generate a high-quality image that incorporates useful information from each image. We found that this technique can enhance image quality and provides an effective way of improving OCR accuracy. Our contributions in this paper are two-fold: (1) a preprocessing chain that uses exposure bracketing techniques for document images is discussed, and an automatic registration method is proposed to find the geometric disparity between multiple document images, which lays the foundation for exposure bracketing; (2) several representative exposure bracketing algorithms are incorporated in the processing chain and their performances are evaluated and compared.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Image and Video Retrieval Techniques · Handwritten Text Recognition Techniques · Image and Object Detection Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Information Science and Engineering, Ocean University of China, Qingdao 266000, China
Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266000, China
Funding
Pilot National Laboratory for Marine Science and Technology (Qingdao) · Qingdao Municipal Science and Technology Bureau
References (17)
Show source-provided references
1. Adaptive binarization of unconstrained hand-held camera-captured document images
2. Adaptive document image binarization10.1016/S0031-3203(99)00055-2 ↗
3. Peters, A.K. (2011). Advanced High Dynamic Range Imaging: Theory and Practice, CRC Press.
4. Block, M., Schaubert, M., Wiesel, F., and Rojas, R. (2009, January 26–29). Multi-Exposure Document Fusion Based on Edge-Intensities. Proceedings of the Theinternational Conference on Document Analysis and Recognition, Barcelona, Spain.10.1109/ICDAR.2009.142 ↗
5. Luqman, M.M., Gomez-Krämer, P., and Ogier, J.M. (2013). Mobile phone camera-based video scanning of paper documents. International Workshop on Camera-Based Document Analysis and Recognition, Springer.10.1007/978-3-319-05167-3_13 ↗
6. Klein, F. (1939). Elementary Mathematics from an Advanced Standpoint, Macmillan.
7. A Review of recent range image registration methods with accuracy evaluation10.1016/j.imavis.2006.05.012 ↗
8. Lowe, D.G. (1999, January 20–27). Object recognition from local scale-invariant features. Proceedings of the International Conference on Computer Vision, Kerkyra, Greece.10.1109/ICCV.1999.790410 ↗
9. Automatic satellite image registration by combination of stereo matching and random sample consensus10.1109/TGRS.2003.811994 ↗
10. Wesley, A., and Whitted, T. (1997). Recovering high dynamic range radiance maps from photographs. SIGGRAPH 97 Conference Proceedings, ACM Siggraph.
11. Devlin, K., Chalmers, A., Wilkie, A., and Purgathofer, W. (2002). Tone Reproduction and Physically Based Spectral Rendering. Eurographics, Available online: https://www.researchgate.net/publication/2539412_Tone_Reproduction_and_Physically_Based_Spectral_Rendering.
12. Photographic Tone Reproduction for Digital Images10.1145/566654.566575 ↗
13. Fast Bilateral Filtering for the Display of High-Dynamic-Range Images10.1145/566654.566574 ↗
14. Exposure Fusion: A Simple and Practical Alternative to High Dynamic Range Photography10.1111/j.1467-8659.2008.01171.x ↗
15. Fusion of multi-exposure images10.1016/j.imavis.2005.02.004 ↗
16. (2019, October 23). GitHub. Available online: https://github.com/tesseract-ocr/tesseract.
17. (2019, October 23). GitHub. Available online: https://github.com/Shreeshrii/ocr-evaluation-tools.