Application of Niblack's Method on Images

被引:14
作者
Farid, S. [1 ]
Ahmed, F. [1 ]
机构
[1] FAST Natl Univ Comp & Emerging Sci Peshawar, Peshawar, Pakistan
来源
ICET: 2009 INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES, PROCEEDINGS | 2009年
关键词
D O I
10.1109/ICET.2009.5353159
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Image segmentation is a major step in image analysis. and processing. Segmentation is performed through several methods. In this work Niblack's method of segmentation is further studied. It is one of the local thresholding techniques for segmentation. The output of Niblack's method is significant and has most acceptable result out of all thresholding techniques in segmenting text documents. In this work the same method is applied on images keeping one of the variables i.e. weight k of Niblack's method Constant while changing the other (window size) from images to images. The output image is better segmented but the background is noisy. Improvements in the resultant images are demonstrated by applying the morphological operations of opening and closing. Opening and closing are combination of two fundamental morphological operations dilation and erosion. Dilation thickens objects in a binary image by adding pixels to the boundaries of the objects, while erosion shrinks objects in a binary image.
引用
收藏
页码:280 / 286
页数:7
相关论文
共 16 条
[1]  
[Anonymous], Digital Image Processing
[2]  
Felzenszwalb P., Efficient Graph-Based Image Segmentation
[3]  
JAGADISH HV, 2001, GLOBAL OPTIMIZATION
[4]  
LEEDHAM G, P 7 INT C DOC AN REC
[5]   Gray-level reduction using local spatial features [J].
Papamarkos, N ;
Atsalakis, A .
COMPUTER VISION AND IMAGE UNDERSTANDING, 2000, 78 (03) :336-350
[6]  
RAIS NB, 2004 IEEE CENT ADV S
[7]   Adaptive document image binarization [J].
Sauvola, J ;
Pietikäinen, M .
PATTERN RECOGNITION, 2000, 33 (02) :225-236
[8]   Survey over image thresholding techniques and quantitative performance evaluation [J].
Sezgin, M ;
Sankur, B .
JOURNAL OF ELECTRONIC IMAGING, 2004, 13 (01) :146-168
[9]  
Shapiro L. G., COMPUTER VISION
[10]   Normalized cuts and image segmentation [J].
Shi, JB ;
Malik, J .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2000, 22 (08) :888-905