Efficient document image binarization using heterogeneous computing and parameter tuning
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[1] Mohamed Akil,et al. GPU parallel implementation of the new hybrid binarization based on Kmeans method (HBK) , 2018, Journal of Real-Time Image Processing.
[2] Ramazan Savas Aygün,et al. Super-Thresholding: Supervised Thresholding of Protein Crystal Images , 2017, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[3] Konstantinos Zagoris,et al. ICFHR2016 Handwritten Document Image Binarization Contest (H-DIBCO 2016) , 2016, 2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR).
[4] Yuefang Gao,et al. CUDA-accelerated fast Sauvola’s method on Kepler architecture , 2015, Multimedia tools and applications.
[5] Rupinder Kaur,et al. Review of Robust Document Image BINARIZATION Technique for Degraded Document Images , 2015 .
[6] Marcus Liwicki,et al. Document Image Binarization using LSTM: A Sequence Learning Approach , 2015, HIP@ICDAR.
[7] Carlos A. B. Mello,et al. Parameter tuning for document image binarization using a racing algorithm , 2015, Expert Syst. Appl..
[8] Clément Chatelain,et al. Exploring multiple feature combination strategies with a recurrent neural network architecture for off-line handwriting recognition , 2015, Electronic Imaging.
[9] Li Chen,et al. JF-Cut: A Parallel Graph Cut Approach for Large-Scale Image and Video , 2015, IEEE Transactions on Image Processing.
[10] Alicia Fornés,et al. A Coarse-to-Fine Word Spotting Approach for Historical Handwritten Documents Based on Graph Embedding and Graph Edit Distance , 2014, 2014 22nd International Conference on Pattern Recognition.
[11] Mohamed Akil,et al. A new hybrid binarization method based on Kmeans , 2014, 2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP).
[12] Carlos A. B. Mello,et al. A new thresholding algorithm for document images based on the perception of objects by distance , 2014, Integr. Comput. Aided Eng..
[13] Josep Lladós,et al. Boosting the handwritten word spotting experience by including the user in the loop , 2014, Pattern Recognit..
[14] Nicholas R. Howe,et al. Document binarization with automatic parameter tuning , 2013, International Journal on Document Analysis and Recognition (IJDAR).
[15] Ioannis Pratikakis,et al. ICDAR 2013 Document Image Binarization Contest (DIBCO 2013) , 2013, 2013 12th International Conference on Document Analysis and Recognition.
[16] Volkmar Frinken,et al. Handwriting recognition in historical documents using very large vocabularies , 2013, HIP '13.
[17] Mohamed Cheriet,et al. A learning framework for the optimization and automation of document binarization methods , 2013, Comput. Vis. Image Underst..
[18] Ioannis Pratikakis,et al. ICFHR 2012 Competition on Handwritten Document Image Binarization (H-DIBCO 2012) , 2012, 2012 International Conference on Frontiers in Handwriting Recognition.
[19] Rahul Sharma,et al. Parallel Implementation of Souvola’s Binarization Approach on GPU , 2011 .
[20] Rahul Sharma,et al. Parallel Implementation of Niblack’s Binarization Approach on CUDA , 2011 .
[21] Nicholas R. Howe,et al. A Laplacian Energy for Document Binarization , 2011, 2011 International Conference on Document Analysis and Recognition.
[22] Ioannis Pratikakis,et al. ICDAR 2011 Document Image Binarization Contest (DIBCO 2011) , 2011, 2011 International Conference on Document Analysis and Recognition.
[23] Daniel Díaz-Pernil,et al. A Parallel Implementation of the Thresholding Problem by Using Tissue-Like P Systems , 2011, CAIP.
[24] Ioannis Pratikakis,et al. DIBCO 2009: document image binarization contest , 2011, International Journal on Document Analysis and Recognition (IJDAR).
[25] Ioannis Pratikakis,et al. H-DIBCO 2010 - Handwritten Document Image Binarization Competition , 2010, 2010 12th International Conference on Frontiers in Handwriting Recognition.
[26] John E. Stone,et al. OpenCL: A Parallel Programming Standard for Heterogeneous Computing Systems , 2010, Computing in Science & Engineering.
[27] Hemant Ishwaran,et al. Random Survival Forests , 2008, Wiley StatsRef: Statistics Reference Online.
[28] P. J. Narayanan,et al. CUDA cuts: Fast graph cuts on the GPU , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.
[29] T. Hothorn,et al. Simultaneous Inference in General Parametric Models , 2008, Biometrical journal. Biometrische Zeitschrift.
[30] Thomas M. Breuel,et al. Efficient implementation of local adaptive thresholding techniques using integral images , 2008, Electronic Imaging.
[31] Richard Szeliski,et al. A Comparative Study of Energy Minimization Methods for Markov Random Fields , 2006, ECCV.
[32] Ioannis Pratikakis,et al. Adaptive degraded document image binarization , 2006, Pattern Recognit..
[33] P. Kohli,et al. Efficiently solving dynamic Markov random fields using graph cuts , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[34] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[35] Vladimir Kolmogorov,et al. An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision , 2001, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[36] Matti Pietikäinen,et al. Adaptive document image binarization , 2000, Pattern Recognit..
[37] Davi Geiger,et al. Segmentation by grouping junctions , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).
[38] Ingemar J. Cox,et al. A maximum-flow formulation of the N-camera stereo correspondence problem , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).
[39] A. Goldberg,et al. A new approach to the maximum-flow problem , 1988, JACM.
[40] John F. Canny,et al. A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[41] Robert M. Haralick,et al. Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..
[42] Richard M. Karp,et al. Theoretical Improvements in Algorithmic Efficiency for Network Flow Problems , 1972, Combinatorial Optimization.
[43] D. R. Fulkerson,et al. Flows in Networks , 1963 .
[44] N. Lavesson,et al. Efficient Binarization for Historical Document Analysis , 2016 .
[45] Nadine Eberhardt,et al. Computer Organization And Design 2nd Edition , 2016 .
[46] Ioannis Pratikakis,et al. ICFHR2014 Competition on Handwritten Document Image Binarization (H-DIBCO 2014) , 2014, 2014 14th International Conference on Frontiers in Handwriting Recognition.
[47] Brij Mohan Singh,et al. Parallel Implementation of Otsu’s Binarization Approach on GPU , 2011 .
[48] Udaya B. Kogalur,et al. Random Survival Forests for R , 2007 .
[49] Rae-Hong Park,et al. Document image binarization based on topographic analysis using a water flow model , 2002, Pattern Recognit..
[50] Richard J. Anderson,et al. Goldberg's Algorithm for Maximum Flow in Perspective: A Computational Study , 1991, Network Flows And Matching.
[51] D. Greig,et al. Exact Maximum A Posteriori Estimation for Binary Images , 1989 .
[52] Wayne Niblack,et al. An introduction to digital image processing , 1986 .
[53] Nobuyuki Otsu,et al. ATlreshold Selection Method fromGray-Level Histograms , 1979 .
[54] N. Otsu. A threshold selection method from gray level histograms , 1979 .