DocumentCode :
1698614
Title :
The edge detection of river model based on self-adaptive Canny Algorithm and connected domain segmentation
Author :
Zhao, Jianjun ; Yu, Heng ; Gu, Xiaoguang ; Wang, Sheng
Author_Institution :
Inst. of Adv. Control & Intell. Inf. Process., Henan Univ., Kaifeng, China
fYear :
2010
Firstpage :
1333
Lastpage :
1336
Abstract :
An image edge detection method of river regime is presented for river model images. This method of self-adaptive thresholding Canny edge detection can extracts the edges of river regime automatically. It not only inherits the advantages of traditional Canny Algorithm, but also uses the improved maximum variance ratio method to calculate the values of Canny gradient threshold self-adaptively. And on this basis, morphological connected domain segmentation be used to suppress the interference edge of the image. This method achieves the automatic identification and extraction of river regime of the model. Tests showed that proposed algorithm has good robustness and high extraction precision, so that the next step of width measurement will be easier and preciser.
Keywords :
edge detection; feature extraction; image segmentation; interference suppression; rivers; connected domain; edge detection; image segmentation; interference suppression; maximum variance ratio method; river model; river regime extraction; river regime identification; self-adaptive thresholding Canny algorithm; Computational modeling; Heuristic algorithms; Histograms; Image edge detection; Image segmentation; Pixel; Rivers; Connected domain; Edge detection; Maximum variance ratio; River model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
Type :
conf
DOI :
10.1109/WCICA.2010.5554869
Filename :
5554869
Link To Document :
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