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