基于区域对比度增强的二值化算法

doi:10.11999/JEIT160197

Abstract
Figure/Table
References (12)
Related Citation (15)

Download: PDF (2564 KB)
Export: BibTeX | EndNote (RIS)

Abstract

Binarization for degraded document images is a difficult point in image processing. This paper presents a new binarization method for the degraded document images by analyzing the differences of image grayscale contrast in different areas. Firstly, theory of quadtree is used to divide areas adaptively. Secondly, various contrast enhancements are selected to adjust local grayscale contrast for different contrast areas. Lastly, the frequency of gray value is utilized to calculate threshold. The proposed algorithm is tested on random shooting degraded images and datasets of Document Image Binarization COntest (DIBCO). Compared with other four classical algorithms, the binaried images using the proposed algorithm gain the highest F-measure and PSNR (Peak Signal-to-Noise Ratio).

Key words： Image processing Binarization Local contrast enhancement Local threshold Quadtree

Received: 03 March 2016 Published: 30 September 2016

PACS:

TN911.73

Fund:

The Science and Technology Innovation Talents Project of Harbin (2014RFQXJ163)

Corresponding Authors: HUANG Xin E-mail: scorpion_hx@163.com

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	LU Di
	HUANG Xin
	LIU Changyuan
	LIN Xue
	ZHANG Huayu
	YAN Jun

Cite this article:

LU Di,HUANG Xin,LIU Changyuan等. Binarization Method Based on Local Contrast Enhancement[J]. JEIT, 2017, 39(1): 240-244.

URL:

http://jeit.ie.ac.cn/EN/10.11999/JEIT160197 OR http://jeit.ie.ac.cn/EN/Y2017/V39/I1/240

[1]	OTSU N. A threshold selection method from gray level histograms[J]. IEEE Transactions on Systems, Man and Cybernetics, 1979, 9(1): 62-66. doi: 10.1109/TSMC.1979. 4310076.
[2]	申铉京, 龙建武, 陈海鹏, 等. 三维直方图重建和降维的Otsu阈值分割算法[J]. 电子学报, 2011, 39(5): 1108-1114.
	SHEN Xuanjing, LONG Jianwu, CHEN Haipeng, et al. Otsu thresholding algorithm based on rebuilding and dimension reduction of the 3-dimensional histogram[J]. Acta Electronica Sinica, 2011, 39(5): 1108-1114.
[3]	NIBLACK W. An Introduction to Digital Image Processing [M]. Englewood Cliffs, NJ, US, Prentice-Hall, Inc., 1986: 115-116.
[4]	SAUVOLA J and PIETIKAINEN M. Adaptive document image binarization[J]. Pattern Recognit, 2000, 33(2): 225-236. doi: 10.1016/S0031-3203(99)00055-2.
[5]	MA L and STAUNTON R C. A modified fuzzy C-means image segmentation algorithm for use with uneven illumination patterns[J]. Pattern Recognition, 2007, 40(11): 3005-3011. doi: 10.1016/j.patcog.2007.02.005.
[6]	CHOU C H, and LIN W H, and CHANG F. A binarization method with learning-build rules for document images produced by cameras[J]. Pattern Recognition, 2010, 43(4): 1518-1530. doi: 10.1016/j.patcog.2009.10.016.
[7]	龙建武, 申铉京, 臧慧, 等. 高斯尺度空间下估计背景的自适应阈值分割算法[J]. 自动化学报, 2014, 40(8): 1773-1782. doi: 10.3724/SP.J.1004.2014.01773.
	LONG Jianwu, SHEN Xuanjing, ZANG Hui, et al. An adaptive thresholding algorithm by background estimation in Gaussian scale space[J]. Acta Automatica Sinica, 2014, 40(8): 1773-1782. doi: 10.3724/SP.J.1004.2014.01773.
[8]	SINGH B M, SHARMA R, GHOSH D, et al. Adaptive binarization of severely degraded and non-uniformly illuminated documents[J]. International Journal of Document Analysis and Recognition, 2014, 17(4): 393-412. doi: 10.1007/ s10032-014-0219-6.
[9]	MESQUITA R G, MELLO C A B, and ALMEIDA L H E V. A new thresholding algorithm for document images based on the perception of objects by distance[J]. Integrated Computer-Aided Engineering, 2014, 21(2): 133-146. doi: 10.3233/ICA-130453.
[10]	MILYAEV S, BARINOVA O, NOVIKOVA T, et al. Fast and accurate scene text understanding with image binarization and off-the-shelf OCR[J]. International Journal of Document Analysis and Recognition, 2015, 18(2): 169-182. doi: 10.1007/ s10032-015-0240-4.
[11]	ROSENFELD A and KAK A C. Digital Picture Processing [M]. 2nd ed. New York, Morgan Kaufmann: Academic Press, 1982: 92-95.
[12]	PRATIKAKIS I, GATOS B, and NTIROGIANNIS K. DIBCO 2013-Document Image Binarization Contest [EB/ OL]. http://utopia.duth.gr/~ipratika/DIBCO2013/, 2013.