NDLI: Application of Improved Snake Model in Segmentation of Korean Pine Cone Image

Content Provider	IEEE Xplore Digital Library
Author	Su Jian-min Wang Xiao-li
Copyright Year	2010
Abstract	In the Korean Pine solid quantity's forecast technique, the characteristic of Korean Pine cone's shape is one of main parameters. This paper can provide the precise data for the Korean Pine solid quantity's forecast technique by segmenting the image of Korean Pine which is taken by the Filed Server. Considering of the complex background of Korean Pine image and the target of hollow contours, we proposed a Snake model image segmentation algorithm that is improved by Ant Colony Algorithm. First, the overall robustness advantage of the Ant Colony Algorithm is used to gain target contours. Then the contours are set to the improved Snake model’s starting value and overcome the original Snake model’s drawbacks. Finally, we can obtain the complete target. The experiment has proven the algorithm’s validity and precision.
Starting Page	68
Ending Page	71
File Size	1039927
Page Count	4
File Format	PDF
ISBN	9781424486267
e-ISBN	9780769542584
DOI	10.1109/MINES.2010.22
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-11-04
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Ant Colony Algorithm Computational modeling Biological system modeling Image edge detection Euclidean distance Korean Pine Cone Solids Mathematical model Snake model Pixel
Content Type	Text
Resource Type	Article

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