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