DocumentCode :
497310
Title :
An Approach for Image Thresholding Using CNN Associated with Histogram Analysis
Author :
Kang, Jiayin ; Zhang, Wenjuan
Author_Institution :
Sch. of Electron. Eng., Huaihai Inst. of Technol., Lianyungang, China
Volume :
1
fYear :
2009
fDate :
11-12 April 2009
Firstpage :
421
Lastpage :
424
Abstract :
Thresholding is one of the old, simple, and popular techniques for image segmentation, and has been widely studied. In this paper, an approach for image thresholding based on cellular neural network (CNN) associated with histogram analysis is presented. The approach realized by threshold CNN (T-CNN), in which the threshold is obtained via histogram-based automatic searching algorithm. Experimental results on real images show that the proposed approach can extract the objects from the background effectively with better visual quality than other methods.
Keywords :
cellular neural nets; image segmentation; T-CNN; cellular neural network; histogram-based automatic searching algorithm; image segmentation; image thresholding; Automation; Cellular neural networks; Histograms; Hopfield neural networks; Image analysis; Image processing; Image segmentation; Mechatronics; Pixel; Robot vision systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on
Conference_Location :
Zhangjiajie, Hunan
Print_ISBN :
978-0-7695-3583-8
Type :
conf
DOI :
10.1109/ICMTMA.2009.311
Filename :
5203002
Link To Document :
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