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Competition on Binarizing Photographed Document Images 2024 Quality, Time and Space Report

Published: 18 September 2024 Publication History

Abstract

Many document processing platforms have image binarization as a key step. The performance of binarization algorithms depends on several factors that span from the quality of the digitalization devices to the intrinsic features of the document itself and the kind and intensity of the noises present in the image. Besides that, the processing time is also an important factor that may restrict the applicability of a given algorithm. This competition on binarizing photographed documents assessed the quality, time, space, and performance of twenty three new algorithms and seventy-five "classical" algorithms. The test dataset is composed of offset and deskjet printed documents, photographed using six widely-used mobile devices with the strobe flash on, off, and in auto modes under two different angles and places of capture.

References

[1]
Younes Akbari et al. 2019. Binarization of Degraded Document Images using Convolutional Neural Networks based on predicted Two-Channel Images. In ICDAR.
[2]
Elisa H. Barney Smith, Laurence Likforman-Sulem, and Jérôme Darbon. 2010. Effect of Pre-processing on Binarization. In Document Recognition and Retrieval XVII. 75340H.
[3]
Bilal Bataineh et al. 2011. An adaptive local bin. method for doc. images based on a novel thresh. method and dynamic windows. Ptrn. Recog. Letters 32, 14 (2011).
[4]
Suman Kumar Bera et al. 2021. A non-parametric binarization method based on ensemble of clustering algorithms. Multimedia Tools and Applications 80, 5 (2021), 7653--7673.
[5]
Rodrigo Bernardino, Rafael Dueire Lins, and Ricardo Barboza. 2024. Texture-based Document Binarization. In Proceedings of ACM Symposium on Document Engineering 2024 (DocEng '24). ACM, New York, NY, USA.
[6]
J Bernsen. 1986. Dynamic thresholding of gray-level images. In International Conference on Pattern Recognition. 1251--1255.
[7]
Showmik Bhowmik, Ram Sarkar, Bishwadeep Das, and David Doermann. 2018. GiB: a Game theory Inspired Binarization technique for degraded document images. IEEE Transactions on Image Processing 28, 3 (2018), 1443--1455.
[8]
Jean-Luc Bloechle, Jean Hennebert, and Christophe Gisler. 2023. YinYang, a Fast and Robust Adaptive Document Image Binarization for Optical Character Recognition. In Proceedings of the ACM Symposium on Document Engineering 2023 (Limerick, Ireland) (DocEng '23). Association for Computing Machinery, Article 19, 4 pages. https://doi.org/10.1145/3573128.3609354
[9]
Jean-Luc Bloechle, Jean Hennebert, and Christophe Gisler. 2024. ZigZag: A Robust Adaptive Approach to Non-Uniformly Illuminated Document Image Binarization. In Proceedings of ACM Symposium on Document Engineering 2024 (DocEng '24). ACM, New York, NY, USA.
[10]
Bolan Su, Shijian Lu, and Chew Lim Tan. 2013. Robust Document Image Binarization Technique for Degraded Document Images. T. on I. Processing 22, 4 (2013), 1408--1417.
[11]
Derek Bradley and Gerhard Roth. 2007. Adaptive Thresholding using the Integral Image. Journal of Graphics Tools 12, 2 (2007), 13--21.
[12]
Jorge Calvo-Zaragoza and Antonio-Javier Gallego. 2019. A selectional auto-encoder approach for document image binarization. Pattern Recognition 86 (2019), 37--47.
[13]
W. Doyle. 1962. Operations Useful for Similarity-Invariant Pattern Recognition. J. ACM 9, 2 (1962), 259--267.
[14]
Rafael Dueire Lins, Rodrigo Bernardino, and Darlisson Marinho Jesus. 2019. A Quality and Time Assessment of Binarization Algorithms. In 2019 International Conference on Document Analysis and Recognition (ICDAR). 1444--1450. https: //doi.org/10.1109/ICDAR.2019.00232
[15]
Abdeljalil Gattal, Faycel Abbas, and Mohamed Ridda Laouar. 2018. Automatic Parameter Tuning of K-Means Algorithm for Document Binarization. In 7th ICSENT. ACM Press, 1--4.
[16]
C Glasbey. 1993. An Analysis of Histogram-Based Thresholding Algorithms. Graphical Models and Image Processing 55, 6 (1993), 532--537.
[17]
Zineb Hadjadj, Abdelkrim Meziane, Yazid Cherfa, Mohamed Cheriet, and Insaf Setitra. [n.d.]. ISauvola: Improved Sauvola's Algorithm for Document Image Binarization. 737--745.
[18]
Sheng He and Lambert Schomaker. 2019. DeepOtsu: Document Enhancement and Binarization using Iterative Deep Learning. Pattern Recognition 91 (jan 2019), 379--390.
[19]
Nicholas R. Howe. 2013. Doc. binarization with automatic parameter tuning. IJDAR 16 (2013).
[20]
Liang Kai Huang and Mao Jiun J. Wang. 1995. Image thresholding by minimizing the measures of fuzziness. Pattern Recognition 28, 1 (1995), 41--51.
[21]
Fuxi Jia, Cunzhao Shi, Kun He, Chunheng Wang, and Baihua Xiao. 2018. Degraded document image binarization using structural symmetry of strokes. Pattern Recognition 74 (2018), 225--240.
[22]
J Johannsen, G and Bille. 1982. A threshold selection method using information measures. In Int'l Conf. Pattern Recognition. 140--143.
[23]
J.N. Kapur, P.K. Sahoo, and A.K.C. Wong. [n.d.]. A new method for gray-level picture thresholding using the entropy of the histogram. C. Vision, Graphics, I. Processing 29, 1 ([n.d.]), 140.
[24]
Ergina Kavallieratou. 2005. A binarization algorithm specialized on document images and photos. ICDAR 2005, 1 (2005), 463--467.
[25]
Ergina Kavallieratou and Stamatatos Stathis. 2006. Adaptive binarization of historical document images. Proceedings - International Conference on Pattern Recognition 3 (2006), 742--745.
[26]
Khurram Khurshid, Imran Siddiqi, Claudie Faure, and Nicole Vincent. 2009. Comparison of Niblack inspired binarization methods for ancient documents. In SPIE. 72470U.
[27]
J. Kittler et al. 1986. Minimum error thresholding. Pattrn. Recog. 19, 1 (1986).
[28]
C.H. Li and P.K.S. Tam. 1998. An iterative algorithm for minimum cross entropy thresholding. Pattern Recognition Letters 19, 8 (1998), 771--776.
[29]
Rafael Dueire Lins. 2009. A Taxonomy for Noise in Images of Paper Documents - The Physical Noises. In Lecture Notes in Computer Science, Vol. 5627 LNCS. 844--854. https://doi.org/10.1007/978-3-642-02611-9_83
[30]
Rafael Dueire Lins, R. B. Bernardino, et al. 2021. DocEng'2021 Direct Binarization A Quality-and-Time Efficient Binarization Strategy. In DocEng 2021. ACM.
[31]
Rafael Dueire Lins, Rodrigo Barros Bernardino, Ricardo Barboza, and Steven J. Simske. 2022. DocEng'2022 Quality, Space, and Time Competition on Binarizing Photographed Documents. In DocEng '22. ACM, 1--4.
[32]
Rafael Dueire Lins, Rodrigo Barros Bernardino, Elisa Barney Smith, and Ergina Kavallieratou. [n.d.]. ICDAR 2021 Competition on Time-Quality Document Image Binarization. In ICDAR 2021. 1539--1546. https://doi.org/10.1007/978-3-030-86337-1_47
[33]
Rafael Dueire Lins, R. B. Bernardino, and et. al. 2017. Binarizing Document Images Acquired with Portable Cameras. In 2017 14th ICDAR. IEEE.
[34]
Rafael Dueire Lins, Rodrigo Barros Bernardino, and Steven J. Simske. 2021. DocEng'2021 Time-Quality Competition on Binarizing Photographed Documents. In DocEng'2021. ACM, 1--4. https://doi.org/10.1145/3395027.3419578
[35]
Rafael Dueire Lins, Gabriel de F. Pe Silva, Gustavo P. Chaves, Ricardo da Silva Barboza, Rodrigo Barros Bernardino, and Steven J. Simske. 2023. Quality, Space and Time Competition on Binarizing Photographed Document Images. In Proceedings of the ACM Symposium on Document Engineering 2023 (Limerick, Ireland) (DocEng '23). Association for Computing Machinery, Article 5, 10 pages. https://doi.org/10.1145/3573128.3604903
[36]
Rafael Dueire Lins, Gabriel de F. Pe Silva, Gustavo P. Chaves, Ricardo da Silva Barboza, Rodrigo Barros Bernardino, and Steven J. Simske. 2023. Quality, Space and Time Competition on Binarizing Photographed Document Images. In Proceedings of the ACM Symposium on Document Engineering 2023 (Limerick, Ireland) (DocEng '23). Association for Computing Machinery, Article 5, 10 pages. https://doi.org/10.1145/3573128.3604903
[37]
Rafael Dueire Lins, Ergina Kavallieratou, Elisa Barney Smith, Rodrigo Barros Bernardino, and Darlisson Marinho de Jesus. [n.d.]. ICDAR 2019 Time-Quality Binarization Competition. In ICDAR. 1539--1546. https://doi.org/10.1109/ICDAR.2019.00248
[38]
Rafael Dueire Lins and Domingos Machado. 2004. Comparative study of file formats for image storage and transmission. Journal of Electronic Imaging 13, 1 (2004), 175 - 181. https://doi.org/10.1117/1.1634591
[39]
Rafael Dueire Lins, Steven J. Simske, and Rodrigo Barros Bernardino. 2020. DocEng'2020 Time-Quality Competition on Binarizing Photographed Documents. In DocEng '20: ACM Symposium on Document Engineering 2020, Virtual Event, CA, USA, September 29 - October 1, 2020. ACM. https://doi.org/10.1145/3395027.3419578
[40]
Di Lu, Xin Huang, and LiXue Xue Sui. 2018. Binarization of degraded document images based on contrast enhancement. IJDAR 21, 1--2 (2018), 123--135.
[41]
Shijian Lu, Bolan Su, and Chew Lim Tan. 2010. Document image binarization using background estimation and stroke edges. IJDAR 13, 4 (2010), 303--314.
[42]
Wu Lu, Ma Songde, and Hanqing Lu. 1998. An effective entropic thresholding for ultrasonic images. 14th ICPR (1998), 1552--1554, vol. 2.
[43]
Carlos A.B. Mello and Rafael Dueire Lins. 2002. Generation of images of historical documents by composition. In DocEng '02: Proceedings of the 2002 ACM symposium on Document engineering. 127--133. https://doi.org/10.1145/585058.585082
[44]
Carlos A. B. Mello and Rafael Dueire Lins. 2000. Image segmentation of historical documents. Visual 2000 (2000).
[45]
Hubert Michalak and Krzysztof Okarma. 2019. Adaptive image binarization based on multi-layered stack of regions. In International Conference on Computer Analysis of Images and Patterns. Springer, 281--293.
[46]
Hubert Michalak and Krzysztof Okarma. 2019. Fast Binarization of Unevenly Illuminated Document Images Based on Background Estimation for Optical Character Recognition Purposes. J. Univers. Comput. Sci. 25, 6 (2019), 627--646.
[47]
Hubert Michalak and Krzysztof Okarma. 2019. Improvement of image binarization methods using image preprocessing with local entropy filtering for alphanumerical character recognition purposes. entropy 21, 6 (2019), 562.
[48]
Wan Azani Mustafa and Mohamed Mydin M. Abdul Kader. 2018. Binarization of Document Image Using Optimum Threshold Modification. J. Physics: C. Series 1019, 1 (2018), 012022.
[49]
Wayne Niblack. 1985. An introduction to digital image processing. Strandberg.
[50]
Nobuyuki Otsu. 1979. A threshold selection method from gray-level histograms. IEEE T. on Systems, Man, and Cybernetics 9, 1 (1979), 62--66.
[51]
Judith M. S. Prewitt and Mortimer L. Mendelsohn. 2006. The Analysis of Cell Images. Annals of the New York Academy of Sciences 128, 3 (2006), 1035--1053.
[52]
T. Pun. 1981. Entropic thresholding, a new approach. Computer Graphics and Image Processing 16, 3 (1981), 210--239.
[53]
A.H. Robinson and C. Cherry. 1967. Results of a prototype television bandwidth compression scheme. Proc. IEEE 55, 3 (1967), 356--364. https://doi.org/10.1109/PROC.1967.5493
[54]
Khairun Saddami, Putri Afrah, Viska Mutiawani, and Fitri Arnia. 2018. A New Adaptive Thresholding Technique for Binarizing Ancient Document. In INAPR. IEEE, 57--61.
[55]
Khairun Saddami, Khairul Munadi, Yuwaldi Away, and Fitri Arnia. 2019. Effective and fast binarization method for combined degradation on ancient documents. Heliyon (2019).
[56]
Khairun Saddami, Khairul Munadi, Sayed Muchallil, and Fitri Arnia. 2017. Improved Thresholding Method for Enhancing Jawi Binarization Performance. In ICDAR, Vol. 1. IEEE.
[57]
Prasanna Sahoo, Carrye Wilkins, and Jerry Yeager. 1997. Threshold selection using Renyi's entropy. Pattern Recognition 30, 1 (1997), 71--84.
[58]
J. Sauvola, M. Pietikäinen, and M Pietikainem. 2000. Adaptive document image binarization. Pattern Recognition 33, 2 (2000), 225--236.
[59]
Jaakko Sauvola, Tapio Seppanen, Sami Haapakoski, and Matti Pietikainen. 1997. Adaptive document binarization. In ICDAR, Vol. 1. IEEE Comput. Soc, 147--152.
[60]
A.G. G Shanbhag. 1994. Utilization of Information Measure as a Means of Image Thresholding. CVGIP: Graphical Models and Image Processing 56, 5 (1994), 414--419.
[61]
J M M Silva, Rafael D. Lins, and Valdemar C Rocha. 2006. Binarizing and Filtering Historical Documents with Back-to-Front Interference. In ACM SAC 2006. 853--858. https://doi.org/10.1145/1141277.1141471
[62]
T. Romen Singh, Sudipta Roy, O. Imocha Singh, Tejmani Sinam, and Kh. Manglem Singh. 2011. A New Local Adaptive Thresholding Technique in Binarization. IJCSI 08, 6 (2011), 271--277.
[63]
Mohamed Ali Souibgui and Yousri Kessentini. 2021. DE-GAN: A Conditional Generative Adversarial Network for Document Enhancement. Ptrn. Analysis and Machine Intellig. (2021).
[64]
Mohamed Ali Souibgui and Yousri Kessentini. 2022. DE-GAN: A Conditional Generative Adversarial Network for Document Enhancement. IEEE Transactions on Pattern Analysis and Machine Intelligence 44, 3 (2022), 1180--1191. https: //doi.org/10.1109/TPAMI.2020.3022406
[65]
Bolan Su, Shijian Lu, and Chew Lim Tan. 2010. Binarization of historical document images using the local maximum and minimum. In 8th IAPR DAS. ACM Press, 159--166.
[66]
Chris Tensmeyer and Tony Martinez. 2017. Document Image Binarization with Fully Convolutional Neural Networks. 99--104. https://doi.org/10.1109/ICDAR.2017.25
[67]
Wen-Hsiang Tsai. 1985. Moment-preserving thresolding: A new approach. Computer Vision, Graphics, and Image Processing 29, 3 (1985), 377--393.
[68]
Flavio R. Velasco. 1979. Thresholding Using the Isodata Clustering Algorithm. Technical Report. OSD or Non-Service DoD Agency. 14 pages.
[69]
ChristianWolf and David Doermann. 2002. Binarization of low quality text using a Markov random field model. In Object recognition supported by user interaction for service robots, Vol. 3. IEEE Comput. Soc, 160--163.
[70]
C. Wolf, J.-M. Jolion, and F. Chassaing. 2002. Text localization, enhancement and binarization in multimedia documents. In 2002 International Conference on Pattern Recognition, Vol. 2. 1037--1040 vol.2. https://doi.org/10.1109/ICPR.2002.1048482
[71]
F J.; Chang S Yen J. C.; Chang, Jui Cheng Yen, Fu Juay Chang, and Shyang Chang. 1995. A New Criterion for Automatic Multilevel Thresholding. T. on Image Processing 4, 3 (1995), 370--378.
[72]
G W Zack, W E Rogers, and S A Latt. 1977. Automatic measurement of sister chromatid exchange frequency. J. Histochemistry and Cytochemistry 25, 7 (1977), 741--753.
[73]
Lichen Zhou et al. 2018. D-linknet: Linknet with pretrained encoder and dilated convolution for satellite imagery road extraction. In Comp. Vision and Ptrn. Recog.

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  1. Competition on Binarizing Photographed Document Images 2024 Quality, Time and Space Report

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    cover image ACM Conferences
    DocEng '24: Proceedings of the ACM Symposium on Document Engineering 2024
    August 2024
    131 pages
    ISBN:9798400711695
    DOI:10.1145/3685650
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    Published: 18 September 2024

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    Author Tags

    1. Binarization
    2. Binarization algorithms
    3. Document Engineering
    4. Photographed Documents
    5. Quality evaluation
    6. Scanned Documents
    7. Space evaluation
    8. Time evaluation

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    DocEng '24
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    DocEng '24: ACM Symposium on Document Engineering 2024
    August 20 - 23, 2024
    CA, San Jose, USA

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    DocEng '24 Paper Acceptance Rate 16 of 27 submissions, 59%;
    Overall Acceptance Rate 194 of 564 submissions, 34%

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