Object-oriented Image Segmentation Based on Canny Algorithm

doi:10.6046/gtzyyg.2011.04.05

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Abstract

Object-oriented image analysis is the current research focus in information extraction,and the image segmentation method is the core technology of the object-oriented method. The effect of the segmentation directly affects the extraction of image objects. In this paper, the authors propose an object-oriented method for image segmentation which combines the advantages of edge detection using Canny operator with the secondary developing functions provided by eCognition Developer 8.0. Tests show that the segmentation method is accurate and reliable,the segmentation result is continuous and can well solve the "flood" and "broken" phenomenon. At the same time,this method that combines the advantages of the object-oriented method can satisfactorily solve the problem of "salt and pepper" and minimizes the impact of noise on the classification so as to extract the interesting object surface features.

Keywords Remote sensing Coal mine Surface collapse ORD boundary extraction

:	TP 751.1
	P 237

Issue Date: 16 December 2011

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	WANG Qin-jun
	CHEN Yu
	LIN Qi-zhong

Cite this article:

WANG Qin-jun,CHEN Yu,LIN Qi-zhong. Object-oriented Image Segmentation Based on Canny Algorithm[J]. REMOTE SENSING FOR LAND & RESOURCES, 2011, 23(4): 26-30.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2011.04.05 OR https://www.gtzyyg.com/EN/Y2011/V23/I4/26

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