{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T13:06:49Z","timestamp":1780492009959,"version":"3.54.1"},"reference-count":91,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2020,5,21]],"date-time":"2020-05-21T00:00:00Z","timestamp":1590019200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Image binarization is one of the key operations decreasing the amount of information used in further analysis of image data, significantly influencing the final results. Although in some applications, where well illuminated images may be easily captured, ensuring a high contrast, even a simple global thresholding may be sufficient, there are some more challenging solutions, e.g., based on the analysis of natural images or assuming the presence of some quality degradations, such as in historical document images. Considering the variety of image binarization methods, as well as their different applications and types of images, one cannot expect a single universal thresholding method that would be the best solution for all images. Nevertheless, since one of the most common operations preceded by the binarization is the Optical Character Recognition (OCR), which may also be applied for non-uniformly illuminated images captured by camera sensors mounted in mobile phones, the development of even better binarization methods in view of the maximization of the OCR accuracy is still expected. Therefore, in this paper, the idea of the use of robust combined measures is presented, making it possible to bring together the advantages of various methods, including some recently proposed approaches based on entropy filtering and a multi-layered stack of regions. The experimental results, obtained for a dataset of 176 non-uniformly illuminated document images, referred to as the WEZUT OCR Dataset, confirm the validity and usefulness of the proposed approach, leading to a significant increase of the recognition accuracy.<\/jats:p>","DOI":"10.3390\/s20102914","type":"journal-article","created":{"date-parts":[[2020,5,21]],"date-time":"2020-05-21T11:31:18Z","timestamp":1590060678000},"page":"2914","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Robust Combined Binarization Method of Non-Uniformly Illuminated Document Images for Alphanumerical Character Recognition"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4888-4303","authenticated-orcid":false,"given":"Hubert","family":"Michalak","sequence":"first","affiliation":[{"name":"Faculty of Electrical Engineering, West Pomeranian University of Technology in Szczecin, 70-313 Szczecin, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6721-3241","authenticated-orcid":false,"given":"Krzysztof","family":"Okarma","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering, West Pomeranian University of Technology in Szczecin, 70-313 Szczecin, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"58","DOI":"10.5755\/j01.eee.21.3.10397","article-title":"Fast statistical image binarization of color images for the recognition of the QR codes","volume":"21","author":"Okarma","year":"2015","journal-title":"Elektron. Ir Elektrotech."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Chen, R., Yu, Y., Xu, X., Wang, L., Zhao, H., and Tan, H.Z. (2019). Adaptive Binarization of QR Code Images for Fast Automatic Sorting in Warehouse Systems. Sensors, 19.","DOI":"10.3390\/s19245466"},{"key":"ref_3","unstructured":"Guizzo, E. (2020, May 20). Superfast Scanner Lets You Digitize Book by Flipping Pages. Available online: https:\/\/spectrum.ieee.org\/automaton\/robotics\/robotics-software\/book-flipping-scanning."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Pratikakis, I., Zagoris, K., Karagiannis, X., Tsochatzidis, L., Mondal, T., and Marthot-Santaniello, I. (2019, January 20\u201325). ICDAR 2019 Competition on Document Image Binarization (DIBCO 2019). Proceedings of the 15th IAPR International Conference on Document Analysis and Recognition (ICDAR), Sydney, Australia.","DOI":"10.1109\/ICDAR.2019.00249"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Pratikakis, I., Zagori, K., Kaddas, P., and Gatos, B. (2018, January 5\u20138). ICFHR 2018 Competition on Handwritten Document Image Binarization (H-DIBCO 2018). Proceedings of the 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), Niagala Falls, NY, USA.","DOI":"10.1109\/ICFHR-2018.2018.00091"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Chaki, N., Shaikh, S.H., and Saeed, K. (2014). Exploring Image Binarization Techniques. Studies in Computational Intelligence, Springer.","DOI":"10.1007\/978-81-322-1907-1"},{"key":"ref_7","unstructured":"Lins, R.D., Kavallieratou, E., Smith, E.B., Bernardino, R.B., and de Jesus, D.M. (2019, January 20\u201325). ICDAR 2019 Time-Quality Binarization Competition. Proceedings of the 15th IAPR International Conference on Document Analysis and Recognition (ICDAR), Sydney, Australia."},{"key":"ref_8","unstructured":"Niblack, W. (1986). An Introduction to Digital Image Processing, Prentice Hall."},{"key":"ref_9","first-page":"309","article-title":"Extraction and recognition of artificial text in multimedia documents","volume":"6","author":"Wolf","year":"2004","journal-title":"Form. Pattern Anal. Appl."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Lins, R., e Silva, G.P., and Gomes e Silva, A.R. (2007, January 23\u201326). Assessing and Improving the Quality of Document Images Acquired with Portable Digital Cameras. Proceedings of the 9th International Conference on Document Analysis and Recognition (ICDAR), Parana, Brazil.","DOI":"10.1109\/ICDAR.2007.4376979"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Alqudah, M.K., Bin Nasrudin, M.F., Bataineh, B., Alqudah, M., and Alkhatatneh, A. (2015, January 21\u201323). Investigation of binarization techniques for unevenly illuminated document images acquired via handheld cameras. Proceedings of the International Conference on Computer, Communications, and Control Technology (I4CT), Kuching, Malaysia.","DOI":"10.1109\/I4CT.2015.7219634"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Lins, R.D., Bernardino, R.B., de Jesus, D.M., and Oliveira, J.M. (2017, January 9\u201315). Binarizing Document Images Acquired with Portable Cameras. Proceedings of the 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), Kyoto, Japan.","DOI":"10.1109\/ICDAR.2017.348"},{"key":"ref_13","unstructured":"Pereira, G., and Lins, R.D. (2007, January 22). PhotoDoc: A Toolbox for Processing Document Images Acquired Using Portable Digital Cameras. Proceedings of the 2nd International Workshop on Camera-Based Document Analysis and Recognition (CBDAR), Curitiba, Brazil."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1007\/s10032-004-0138-z","article-title":"Camera-based analysis of text and documents: A survey","volume":"7","author":"Liang","year":"2005","journal-title":"Int. J. Doc. Anal. Recognit."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1109\/TIP.2012.2219550","article-title":"Performance evaluation methodology for historical document image binarization","volume":"22","author":"Ntirogiannis","year":"2013","journal-title":"IEEE Trans. Image Process."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1016\/j.ipm.2009.03.002","article-title":"A systematic analysis of performance measures for classification tasks","volume":"45","author":"Sokolova","year":"2009","journal-title":"Inf. Process. Manag."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1109\/LSP.2003.821748","article-title":"Distance-reciprocal distortion measure for binary document images","volume":"11","author":"Lu","year":"2004","journal-title":"IEEE Signal Process. Lett."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Michalak, H., and Okarma, K. (2019). Improvement of Image Binarization Methods Using Image Preprocessing with Local Entropy Filtering for Alphanumerical Character Recognition Purposes. Entropy, 11.","DOI":"10.3390\/e21060562"},{"key":"ref_19","first-page":"627","article-title":"Fast Binarization of Unevenly Illuminated Document Images Based on Background Estimation for Optical Character Recognition Purposes","volume":"25","author":"Michalak","year":"2019","journal-title":"J. Univ. Comput. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1007\/978-3-030-29891-3_25","article-title":"Adaptive Image Binarization Based on Multi-layered Stack of Regions","volume":"Volume 11679","author":"Vento","year":"2019","journal-title":"Computer Analysis of Images and Patterns"},{"key":"ref_21","unstructured":"dos Anjos, A., and Shahbazkia, H.R. (2008, January 28\u201331). Bi-Level Image Thresholding-A Fast Method. Proceedings of the 1st International Conference on Biomedical Electronics and Devices (BIOSIGNALS), Funchal, Madeira, Portugal."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/0031-3203(86)90030-0","article-title":"Minimum error thresholding","volume":"19","author":"Kittler","year":"1986","journal-title":"Pattern Recognit."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1016\/0031-3203(89)90029-0","article-title":"Improvement of Kittler and Illingworth\u2019s minimum error thresholding","volume":"22","author":"Cho","year":"1989","journal-title":"Pattern Recognit."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","article-title":"A threshold selection method from gray-level histograms","volume":"9","author":"Otsu","year":"1979","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/0734-189X(85)90125-2","article-title":"A new method for gray-level picture thresholding using the entropy of the histogram","volume":"29","author":"Kapur","year":"1985","journal-title":"Comput. Vis. Gr. Image Process."},{"key":"ref_26","first-page":"71","article-title":"Binarization of document images using the modified local-global Otsu and Kapur algorithms","volume":"91","author":"Lech","year":"2015","journal-title":"Przegl\u0105d Elektrotech."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"630","DOI":"10.1109\/TSMC.1978.4310039","article-title":"Picture Thresholding Using an Iterative Selection Method","volume":"8","author":"Ridler","year":"1978","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"793","DOI":"10.1016\/j.patrec.2012.01.002","article-title":"Ridler and Calvard\u2019s, Kittler and Illingworth\u2019s and Otsu\u2019s methods for image thresholding","volume":"33","author":"Xue","year":"2012","journal-title":"Pattern Recognit. Lett."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2083","DOI":"10.1016\/S0031-3203(00)00136-9","article-title":"Unimodal thresholding","volume":"34","author":"Rosin","year":"2001","journal-title":"Pattern Recognit."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1010","DOI":"10.1016\/j.patrec.2009.12.025","article-title":"Robust threshold estimation for images with unimodal histograms","volume":"31","author":"Coudray","year":"2010","journal-title":"Pattern Recognit. Lett."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2419","DOI":"10.1016\/j.patcog.2011.12.013","article-title":"AdOtsu: An adaptive and parameterless generalization of Otsu\u2019s method for document image binarization","volume":"45","author":"Moghaddam","year":"2012","journal-title":"Pattern Recognit."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1518","DOI":"10.1016\/j.patcog.2009.10.016","article-title":"A binarization method with learning-built rules for document images produced by cameras","volume":"43","author":"Chou","year":"2010","journal-title":"Pattern Recognit."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1016\/j.ijleo.2018.02.072","article-title":"Degraded historical document image binarization using local features and support vector machine (SVM)","volume":"164","author":"Xiong","year":"2018","journal-title":"Optik"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Michalak, H., and Okarma, K. (2018, January 9\u201312). Region based adaptive binarization for optical character recognition purposes. Proceedings of the International Interdisciplinary PhD Workshop (IIPhDW), \u015awinouj\u015bcie, Poland.","DOI":"10.1109\/IIPHDW.2018.8388391"},{"key":"ref_35","first-page":"79","article-title":"Fast adaptive image binarization using the region based approach","volume":"Volume 764","author":"Silhavy","year":"2019","journal-title":"Artificial Intelligence and Algorithms in Intelligent Systems"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1016\/0165-1684(80)90020-1","article-title":"A new method for grey-level picture thresholding using the entropy of the histogram","volume":"2","author":"Pun","year":"1980","journal-title":"Signal Process."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1016\/0146-664X(81)90038-1","article-title":"Entropic thresholding, a new approach","volume":"16","author":"Pun","year":"1981","journal-title":"Comput. Gr. Image Process."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Tian, X., and Hou, X. (2009, January 10\u201311). A Tsallis-entropy image thresholding method based on two-dimensional histogram obique segmentation. Proceedings of the 2009 WASE International Conference on Information Engineering, Taiyuan, Chanxi, China.","DOI":"10.1109\/ICIE.2009.42"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Le, T.H.N., Bui, T.D., and Suen, C.Y. (2011, January 18\u201321). Ternary entropy-based binarization of degraded document images using morphological operators. Proceedings of the 11th IAPR International Conference on Document Analysis and Recognition (ICDAR), Beijing, China.","DOI":"10.1109\/ICDAR.2011.32"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1101","DOI":"10.1016\/0167-8655(96)00056-6","article-title":"Image sequence segmentation based on 2D temporal entropic thresholding","volume":"17","author":"Fan","year":"1996","journal-title":"Pattern Recognit. Lett."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/0734-189X(89)90051-0","article-title":"Automatic thresholding of gray-level pictures using two-dimensional entropy","volume":"47","author":"Abutaleb","year":"1989","journal-title":"Comput. Vis. Gr. Image Process."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1131","DOI":"10.1016\/j.knosys.2011.02.013","article-title":"An improved scheme for minimum cross entropy threshold selection based on genetic algorithm","volume":"24","author":"Tang","year":"2011","journal-title":"Knowl.-Based Syst."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.ijleo.2019.02.004","article-title":"A multilevel color image thresholding scheme based on minimum cross entropy and alternating direction method of multipliers","volume":"183","author":"Li","year":"2019","journal-title":"Optik"},{"key":"ref_44","unstructured":"Bernsen, J. (1986, January 27\u201331). Dynamic thresholding of grey-level images. Proceedings of the 8th International Conference on Pattern Recognition (ICPR), Paris, France."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Yang, L., and Feng, Q. (2018, January 23\u201325). The Improvement of Bernsen Binarization Algorithm for QR Code Image. Proceedings of the 5th International Conference on Cloud Computing and Intelligence Systems (CCIS), Nanjing, China.","DOI":"10.1109\/CCIS.2018.8691255"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1080\/2151237X.2007.10129236","article-title":"Adaptive thresholding using the integral image","volume":"12","author":"Bradley","year":"2007","journal-title":"J. Gr. Tools"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Shafait, F., Keysers, D., and Breuel, T.M. (2008, January 27\u201331). Efficient implementation of local adaptive thresholding techniques using integral images. Proceedings of the Document Recognition and Retrieval XV, San Jose, CA, USA.","DOI":"10.1117\/12.767755"},{"key":"ref_48","first-page":"7247","article-title":"Comparison of Niblack inspired binarization methods for ancient documents","volume":"Volume 7247","author":"Khurshid","year":"2009","journal-title":"Document Recognition and Retrieval XVI"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/S0031-3203(99)00055-2","article-title":"Adaptive document image binarization","volume":"33","author":"Sauvola","year":"2000","journal-title":"Pattern Recognit."},{"key":"ref_50","unstructured":"Feng, M.L., and Tan, Y.P. (2004, January 27\u201330). Adaptive binarization method for document image analysis. Proceedings of the 2004 IEEE International Conference on Multimedia and Expo (ICME), Taipei, Taiwan."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1007\/s10032-013-0209-0","article-title":"Efficient multiscale Sauvola\u2019s binarization","volume":"17","author":"Lazzara","year":"2014","journal-title":"Int. J. Doc. Anal. Recognit."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1016\/j.patcog.2005.09.010","article-title":"Adaptive degraded document image binarization","volume":"39","author":"Gatos","year":"2006","journal-title":"Pattern Recognit."},{"key":"ref_53","first-page":"271","article-title":"A New Local Adaptive Thresholding Technique in Binarization","volume":"8","author":"Singh","year":"2011","journal-title":"IJCSI Int. J. Comput. Sci. Issues"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"737","DOI":"10.1007\/978-3-319-41501-7_82","article-title":"ISauvola: Improved Sauvola\u2019s Algorithm for Document Image Binarization","volume":"Volume 9730","author":"Campilho","year":"2016","journal-title":"Image Analysis and Recognition"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"He, Y., and Yang, Y. (2019, January 18\u201320). An Improved Sauvola Approach on QR Code Image Binarization. Proceedings of the 11th International Conference on Advanced Infocomm Technology (ICAIT), Jinan, China.","DOI":"10.1109\/ICAIT.2019.8935907"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"012022","DOI":"10.1088\/1742-6596\/1019\/1\/012022","article-title":"Binarization of Document Image Using Optimum Threshold Modification","volume":"1019","author":"Kader","year":"2018","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_57","unstructured":"Kulyukin, V., Kutiyanawala, A., and Zaman, T. (2012, January 16\u201319). Eyes-free barcode detection on smartphones with Niblack\u2019s binarization and Support Vector Machines. Proceedings of the 16th International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV\u20192012), Las Vegas, NV, USA."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"548","DOI":"10.1134\/S1054661816030020","article-title":"Fast implementation of the Niblack binarization algorithm for microscope image segmentation","volume":"26","author":"Samorodova","year":"2016","journal-title":"Pattern Recognit. Image Anal."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1805","DOI":"10.1016\/j.patrec.2011.08.001","article-title":"An adaptive local binarization method for document images based on a novel thresholding method and dynamic windows","volume":"32","author":"Bataineh","year":"2011","journal-title":"Pattern Recognit. Lett."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Mysore, S., Gupta, M.K., and Belhe, S. (2016, January 11\u201312). Complex and degraded color document image binarization. Proceedings of the 3rd International Conference on Signal Processing and Integrated Networks (SPIN), Noida, India.","DOI":"10.1109\/SPIN.2016.7566680"},{"key":"ref_61","unstructured":"Leedham, G., Yan, C., Takru, K., Tan, J.H.N., and Mian, L. (2003, January 6). Comparison of some thresholding algorithms for text\/background segmentation in difficult document images. Proceedings of the 7th International Conference on Document Analysis and Recognition (ICDAR), Edinburgh, UK."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1117\/1.1631315","article-title":"Survey over image thresholding techniques and quantitative performance evaluation","volume":"13","author":"Sezgin","year":"2004","journal-title":"J. Electron. Imaging"},{"key":"ref_63","first-page":"357","article-title":"A review on pixel-based binarization of gray images","volume":"Volume 439","author":"Shrivastava","year":"2016","journal-title":"ICICT 2015"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Saxena, L.P. (2017). Niblack\u2019s binarization method and its modifications to real-time applications: A review. Artif. Intell. Rev., 1\u201333.","DOI":"10.1007\/s10462-017-9574-2"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"012023","DOI":"10.1088\/1742-6596\/1019\/1\/012023","article-title":"Binarization of document images: A comprehensive review","volume":"1019","author":"Mustafa","year":"2018","journal-title":"J. Phys. Conf. Series"},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Sulaiman, A., Omar, K., and Nasrudin, M.F. (2019). Degraded historical document binarization: A review on issues, challenges, techniques, and future directions. J. Imaging, 5.","DOI":"10.3390\/jimaging5040048"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"1408","DOI":"10.1109\/TIP.2012.2231089","article-title":"Robust document image binarization technique for degraded document images","volume":"22","author":"Su","year":"2013","journal-title":"IEEE Trans. Image Process."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"266","DOI":"10.1016\/j.jvcir.2015.07.003","article-title":"Adaptive-interpolative binarization with stroke preservation for restoration of faint characters in degraded documents","volume":"31","author":"Bag","year":"2015","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Howe, N.R. (2011, January 18\u201321). A Laplacian energy for document binarization. Proceedings of the 11th IAPR International Conference on Document Analysis and Recognition (ICDAR), Beijing, China.","DOI":"10.1109\/ICDAR.2011.11"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1007\/s10032-010-0130-8","article-title":"Document image binarization using background estimation and stroke edges","volume":"13","author":"Lu","year":"2010","journal-title":"Int. J. Doc. Anal. Recognit."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Erol, B., Ant\u00fanez, E.R., and Hull, J.J. (2008, January 26\u201331). HOTPAPER: Multimedia interaction with paper using mobile phones. Proceedings of the 16th International Conference on Multimedia 2008, Vancouver, BC, Canada.","DOI":"10.1145\/1459359.1459413"},{"key":"ref_72","unstructured":"Okamoto, A., Yoshida, H., and Tanaka, N. (2013, January 20\u201323). A binarization method for degraded document images with morphological operations. Proceedings of the 13th IAPR International Conference on Machine Vision Applications (MVA), Kyoto, Japan."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"82","DOI":"10.5755\/j01.eie.24.3.20982","article-title":"Improved degraded document image binarization using median filter for background estimation","volume":"24","author":"Khitas","year":"2018","journal-title":"Elektron. Ir Elektrotech."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"1670","DOI":"10.1016\/j.patcog.2012.11.027","article-title":"A new binarization method for non-uniform illuminated document images","volume":"46","author":"Wen","year":"2013","journal-title":"Pattern Recognit."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.imavis.2015.04.003","article-title":"Document image binarization using local features and Gaussian mixture modeling","volume":"38","author":"Mitianoudis","year":"2015","journal-title":"Image Vis. Comput."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1016\/j.neucom.2016.12.058","article-title":"Broken and degraded document images binarization","volume":"237","author":"Chen","year":"2017","journal-title":"Neurocomputing"},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Lelore, T., and Bouchara, F. (2011, January 18\u201321). Super-resolved binarization of text based on the FAIR algorithm. Proceedings of the 11th IAPR International Conference on Document Analysis and Recognition (ICDAR), Beijing, China.","DOI":"10.1109\/ICDAR.2011.172"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"926","DOI":"10.1016\/j.jvcir.2013.06.001","article-title":"Gradient based adaptive thresholding","volume":"24","author":"Yazid","year":"2013","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1016\/j.neucom.2018.09.087","article-title":"A novel variational model for noise robust document image binarization","volume":"325","author":"Feng","year":"2019","journal-title":"Neurocomputing"},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Almeida, M., Lins, R.D., Bernardino, R., Jesus, D., and Lima, B. (2018). A New Binarization Algorithm for Historical Documents. J. Imaging, 4.","DOI":"10.3390\/jimaging4020027"},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Tensmeyer, C., and Martinez, T. (2017, January 9\u201315). Document image binarization with fully convolutional neural networks. Proceedings of the 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), Kyoto, Japan.","DOI":"10.1109\/ICDAR.2017.25"},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1016\/j.patcog.2017.08.025","article-title":"Binarization of degraded document images based on hierarchical deep supervised network","volume":"74","author":"Vo","year":"2018","journal-title":"Pattern Recognit."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1007\/s12530-017-9200-1","article-title":"Producing fuzzy inclusion and entropy measures and their application on global image thresholding","volume":"9","author":"Bogiatzis","year":"2018","journal-title":"Evol. Syst."},{"key":"ref_84","doi-asserted-by":"crossref","unstructured":"Bogiatzis, A., and Papadopoulos, B. (2019). Global Image Thresholding Adaptive Neuro-Fuzzy Inference System Trained with Fuzzy Inclusion and Entropy Measures. Symmetry, 11.","DOI":"10.3390\/sym11020286"},{"key":"ref_85","doi-asserted-by":"crossref","unstructured":"Jia, F., Shi, C., He, K., Wang, C., and Xiao, B. (2016, January 23\u201326). Document Image Binarization Using Structural Symmetry of Strokes. Proceedings of the 15th International Conference on Frontiers in Handwriting Recognition (ICFHR), Shenzhen, China.","DOI":"10.1109\/ICFHR.2016.0083"},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.patcog.2017.09.032","article-title":"Degraded document image binarization using structural symmetry of strokes","volume":"74","author":"Jia","year":"2018","journal-title":"Pattern Recognit."},{"key":"ref_87","unstructured":"Lins, R.D., Bernardino, R.B., and de Jesus, D.M. (2019, January 20\u201325). A Quality and Time Assessment of Binarization Algorithms. Proceedings of the 15th IAPR International Conference on Document Analysis and Recognition (ICDAR), Sydney, Australia."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"491","DOI":"10.4218\/etrij.13.0112.0545","article-title":"Best combination of binarization methods for license plate character segmentation","volume":"35","author":"Yoon","year":"2013","journal-title":"ETRI J."},{"key":"ref_89","doi-asserted-by":"crossref","unstructured":"Smith, R. (2007, January 23\u201326). An Overview of the Tesseract OCR Engine. Proceedings of the 9th International Conference on Document Analysis and Recognition (ICDAR), Parana, Brazil.","DOI":"10.1109\/ICDAR.2007.4376991"},{"key":"ref_90","doi-asserted-by":"crossref","unstructured":"Deng, F., Wu, Z., Lu, Z., and Brown, M.S. (2010, January 21\u201325). Binarizationshop: A user assisted software suite for converting old documents to black-and-white. Proceedings of the Annual Joint Conference on Digital Libraries, Gold Coast, Queensland, Australia.","DOI":"10.1145\/1816123.1816161"},{"key":"ref_91","unstructured":"Wellner, P.D. (1993). Adaptive Thresholding for the DigitalDesk, Rank Xerox Ltd.. Technical Report EPC 1993-110."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/10\/2914\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:31:05Z","timestamp":1760175065000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/10\/2914"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,21]]},"references-count":91,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2020,5]]}},"alternative-id":["s20102914"],"URL":"https:\/\/doi.org\/10.3390\/s20102914","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,21]]}}}