Image Enhancement Background for High Damage Malay Manuscripts using Adaptive Threshold Binarization

Sitti Rachmawati Yahya, Khairuddin Omar, Siti Norul Huda Sheikh Abdullah, Ali Sophian


Jawi Manuscripts handwritten which are kept at Malaysia National Library (MNL), has aged over decades. Regardless of the intensive sustainable process conducted by MNL, these manuscripts are still not maintained in good quality, and neither can easily be read nor better view. Even thought, many states of the art methods have developed for image enhancement, none of them can solve extremely bad quality manuscripts. The quality of old Malay Manuscripts can be categorize into three types, namely: the background image is uneven, image effects and image effects expand patch. The aim of this paper is to discuss the methods used to value add the quality of the manuscript.  Our propose methods consist of several main methods, such as: Local Adaptive Equalization, Image Intensity Values, Automatic Threshold PP, and Adaptive Threshold Filtering. This paper is intend to achieve a better view image that geared to ease reading. Error Bit Phase achievement (TKB) has a smaller error value for proposed method (Adaptive Threshold Filtering Process / PAM) namely 0.0316 compared with Otsu’s Threshold Method / MNAO, Binary Threshold Value Method / MNAP, and Automatic Local Threshold Value Method / MNATA. The precision achievement (namely on ink bleed images) is using a proposed method more than 95% is compared with the state of the art methods MNAO, MNAP, MNATA and their performances are 75.82%, 90.68%, and 91.2% subsequently.  However, this paper’s achievement is using a proposed method / PAM, MNAO, MNAP, and MNATA for correspondingly the image of ink bleed case are 45.74%, 54.80%, 53.23% and 46.02%.  Conclusion, the proposed method produces a better character shape in comparison to other methods.


Adaptive Equalization, Automatic Threshold, Ink Bleed, Malay Manuscript

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E. Ahmadia, Z. Azimifara, M. Shamsa, M. Famouria, and M. J. Shafiee, “Document image binarization using a discriminative structural classifierâ€, Pattern Recognition Letters, vol. 63, pp. 36–42, June. 2015.

F. Kasmin, A. Abdullah, and A.S. Prabuwono, “Weight determination for supervised binarization algorithm based on QR decompositionâ€, Jurnal Teknologi UTM, vol. 79, pp. 97-106, January 2017.

Al-Qudah, M. K., M. Nasrudin, B. Bataineh, and K. Omar, “A Novel simple thresholding for uneven illuminated document images captured via handheld devicesâ€, Asian Journal of Information Technology, vol. 15(16), pp. 2927-2936, 2016.

T. Celik, “Spatial entropy-based global and local image contrast enhancementâ€, IEEE Transactions on Image Processing, vol. 23(12), pp. 5298-5308, Dec. 2014.

Y. Chen, and L. Wang, “Broken and degraded document images binarizationâ€, Neurocomputing Journal, vol. 237, pp. 272-280, May 2017.

Manuscripts, National Library of Malaysia (Perpustakaan Negara Malaysia, PNM) (April 27, 2009),

X. Fu, D. Zeng, Y. Huang, Y. Liao, X. Ding, and J. Paisley, “A fusion-based enhancing method for weakly illuminated imagesâ€, Signal Processing Journal, Elsevier, vol. 129, pp. 82-96, December 2016.

R. Gal, N. Kiryati, and N. Sochen, “Progress in the restoration of image sequences degraded by atmospheric turbulenceâ€, Pattern Recognition Letters, vol. 48, pp. 8-14, Oct. 2014.

N. Mitianoudis, and N. Papamarkos, †Document image binarization using local features and gaussian mixture modellingâ€, Journal of Image and Vision Computing, vol. 38(c), June 2015.

H. Z. Nafchi, R. F. Moghaddam, and M. Cheriet, “Phase-Based binarization of ancient document images: model and applicationsâ€, IEEE Transactions on Image Processing, vol. 23(7), pp. 2916-2930, July 2014.

J. Natarajan, and I. Sreedevi, “Enhancement of ancient manuscript images by log based binarization techniqueâ€, vol. 75, pp. 15-22, May 2017.

J. Parker, O. Frieder, and G. Frieder, “Automatic enhancement and binarization of degraded document imagesâ€, Conference: Document Analysis and Recognition (ICDAR), August 2013.

S. S. Negi, and Y. S. Bhandari, “A hybrid approach to Image enhancement using contrast stretching on image sharpening and the analysis of various cases arising using histogramâ€, International Conference on Recent Advances and Innovations in Engineering (ICRAIE), IEEE, 2014.

S. R. Yahya, S. N. H. Sheikh Abdullah, K. Omar, M. S. Zakaria, and C. Y. Liong, “Review on image enhancement methods of old manuscript with damaged backgroundâ€, International Journal on Electrical Engineering and Informatics, vol. 2(1), January 2010.

Munteanu, and A. Rosa, “Gray-scale image enhancement as an automatic process driven by evolutionâ€, IEEE Transactions on Systems, Man, and Cybernetics, vol. 34(2), April 2004.

N. Mokhtar, N. H. Harun, M. Y. Mashor, Roseline, N. Mustafa, R. Adollah, Adillah, and N. F. M. Nasir, “Image enhancement techniques using local, global, bright, dark, and partial contrast stretching for acute leukemia Imagesâ€, Proceedings of the World Congress on Engineering (WCE), vol. 1, London UK, July 2009.

S. Roy, P. Shivakumara, H. A. Jalab, R. W. Ibrahim, U. Pal, and T. Lu, “Fractional poisson enhancement model for text detection and recognition in video framesâ€, Pattern Recognition, vol. 52, pp. 433-447, 2016.

[7][8][9][10][11][12][13][14][15][16][17][18]M. K. Alqudah, M. F. Nasrudin, B. Bataimeh, M. Alqudah, and A. Alkhatatneh, “Investigation of binarization techniques for unevenly illuminated document images acquired via handheld camerasâ€, International Conference on Computer, Communications, and Control Technology (I4CT), pp. 524-529, 2015.

S. He, P. Samara, J. Burgers, and L. Schomaker, “A Multiple-label guided clustering algorithm for historical document dating and localizationâ€, IEEE Transactions on Image Processing, vol. 25(11), pp. 5252-5265, Nov. 2016.

J. Wen, S. Li, and J. Sun, “A new binarization method for non-uniform illuminated document imageâ€, Pattern Recognition, vol. 46(6), pp. 1670-1690, June 2013.

D. N. Satange, S. S. Bobde, and S. D. Chikate, “Historical document preservation using image processing techniqueâ€, International Journal of Computer Science and Mobile Computing, vol. 2(4), pp. 247-255, April 2013.

B. Bataineh, S. N. H. S. Abdullah, and K. Omar, “Adaptive binarization method for degraded document images based on surface contrast variationâ€, Pattern Analysis and Applications, vol. 20(3), pp. 639-652, August. 2017.

J. T. Bushberg, J. A. Seiert, E. M. Leidholdt JR, and J. M. Boone, “The essential physics of medical imagingâ€, (2e), European Journal Of Nuclear Medicine And Molecular Imaging, Philadelphia: Lippincott Williams & Wilkins, vol. 30(12), pp. 280, 2002.

G. Breed, “Bit error rate: Fundamental concepts and measurement issuesâ€, High Frequency Electronics, 2003.

K. A. Phillips, J. H. Reed, and W. H. Tranter, “Minimum BER adaptive filteringâ€, IEEE International Conference on ICC, vol. 3, pp. 1675-1680, June 2000.

N. Otsu, “A threshold selection method from gray-level histogramsâ€, IEEE Trans. Sys., Man., Cyber, vol. 9, Pp. 62–66, 1979.

Q. Chen, Q. Sun, P. A. Heng, and D. S. Xia, “A double threshold Image Binarization Method Based on Edge Detectorâ€, Pattern Recognition, vol. 41(4), pp. 1254–1267.

N. Ray, and B. N. Saha, “Edge sensitive variational image thresholdingâ€, IEEE International Conference Image Processing, (ICIP 2007), vol. 6, pp. 37-40, 2007.

W. Boussellaa, A. Bougacha, A. Zahour, H. El Abed, and A. Alimi, “Enhanced text extraction from arabic degraded document images using EM Algorithmâ€, International Conference on Document Anlaysis and Recognition (ICDAR), pp. 743-747, 2009.

C. C. Fung, and R. Chamchong, “A Review of evaluation of optimal binarization technique for character segmentation in historical manuscriptsâ€, Third International Conference on Knowledge Discovery and Data Mining, pp. 236-240, 2010.

Otsu, N, “A threshold selection method from gray-level histogramsâ€, IEEE Trans. Sys., Man., Cyber, vol. 9, pp. 62–66, 1979.

D. Albashish, S. Sahran, A. Abdullah, N. A. Shukor, and H. S. M. Pauzi, “Lumen-nuclei ensemble machine learning system for diagnosing prostate cancer in histopathology imagesâ€, Pertanika J. Sci. & Technol, vol. 25 (S), pp. 39 – 48, 2017.

A. Qasem, S. N. H. Sheikh Abdullah, S. Sahran, R. I. Hussain, “An Accurate rejection model for false positive reduction of mass localization in mammogramâ€, Pertanika J. Sci. & Technol, vol. 25(S), pp. 49 – 62, 2017.

A. B. Al-Naqeeb, and M. J. Nordin, “Robustness watermarking authentication using hybridisation DWT-DCT and DWT-SVDâ€, Pertanika J. Sci. & Technol, vol. 25(S), pp. 73 – 86, 2017.

S. M. M. Kahaki, M. J. Nordin, W. Ismail, S. J. Zahra, R. Hassan, “Blood cancer cell classification based on geometric mean transform and dissimilarity metricsâ€, Pertanika Journal of Science and Technology, vol. 25(S6), pp. 223-234, June 2017.

S. Hakak, A. Kamsin, J. Veri, R. Ritonga, T. Herawan, “A Framework for Authentication of Digital Quranâ€, Information Systems Design and Intelligent Applications. Advances in Intelligent Systems and Computing, vol. 672, Springer, Singapore, March 2018.

N. A. Arbain, M. S. Azmi, S. S. S. Ahmad, R. Nordin, M. Z. Mas'Ud and M. A. Lateh, “Detection on Straight Line Problem in Triangle Geometry Features for Digit Recognitionâ€, International Journal on Advanced Science, Engineering and Information Technology, vol. 6(6), pp. 1019-1025, December 2016.

A. Othman, T. S. M. T. Wook, and S. M. Arif, “Quantization selection of colour histogram bins to categorize the colour appearance of landscape paintings for image retrievalâ€, International Journal on Advanced Science, Engineering and Information Technology, vol. 6(6), pp. 930-936, December 2016.

J. Na`am, J. Harlan, S. Madenda, and E. P. Wibowo, “The algorithm of image edge detection on panoramic dental X-Ray using multiple morphological gradient (MMG) methodâ€, International Journal on Advanced Science, Engineering and Information Technology, vol. 6(6), pp. 1012-1018, December 2016.

M. Lazim, M. F. Nasirudin, and S. N. H. Sheikh Abdullah, “A study of atmospheric particles removal in a low visibility outdoor single imageâ€, International Journal on Advanced Science, Engineering and Information Technology, vol. 6(6), pp. 1081-1088, December 2016.

K. S. Kumar, and G. Sreenivasulu, “Image enhancement through denoising and retrieval of vegetation parameters from landsat8â€, International Journal on Advanced Science, Engineering and Information Technology, vol. 8(1), pp. 199-204, 2018.



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