Title :
Complicated Image´s Binarization Based on Method of Maximum Variance
Author :
Bai, Jie ; Yang, Yao-Quan ; Tian, Rui-li
Author_Institution :
North China Electr. Power Univ.
Abstract :
Image binarization is an important preceding task in image processing and analysis. But the effect of common methods such as Ostu and Bernen are not well when the image´s luminance isn´t equal or the contrast is deficient etc. So, a binarization method based on spatial distributing and improved maximum variance is used in this paper. This method combined the characteristic of image´s spatial distributing and the statistic characteristic of maximum variance in and between clusters. The processing speed is much faster, and artifacts and broken strokes are eliminated
Keywords :
image processing; pattern clustering; statistical analysis; complicated image binarization; image processing; maximum variance; spatial distribution; statistic characteristic; Analysis of variance; Character recognition; Clustering algorithms; Cybernetics; Differential equations; Histograms; Image analysis; Image processing; Machine learning; Pixel; Statistical distributions; Target recognition; Bayes Algorithm; Binarization; Maximum variance between clusters; Threshold;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.258683
