DocumentCode :
173216
Title :
Anisotropic fractal snakes
Author :
Smith, C.E.
Author_Institution :
Sch. of Math. & Comput. Sci., Lake Super. State Univ., Sault Ste. Marie, MI, USA
fYear :
2014
fDate :
5-8 Oct. 2014
Firstpage :
525
Lastpage :
530
Abstract :
The segmentation and tracking of visual patterns, particularly those patterns related to natural imagery, have sparked renewed interest in the computer vision and image processing communities. Applications in robotics, automated systems, geographical information systems, etc. require efficient and accurate methods for processing visual data. Prior work in textural analysis has led to systems with promising accuracy, but poor efficiency. Work on fractal snakes provided both accuracy and efficiency, but at the loss of orientation with respect to the texture. In many applications, resolving orientation is an important piece of information. We have built upon our work in fractal snakes to expand our snake models from a purely isotropic measure of surface roughness to an orientation sensitive model: the Anisotropic Fractal Snake.
Keywords :
computer vision; fractals; image segmentation; image texture; object tracking; zoology; anisotropic fractal snakes; computer vision; image processing; image texture; natural imagery; orientation sensitive model; pattern segmentation; pattern tracking; zebra image; Conferences; Cybernetics; computer vision; fractals; image processing texture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference on
Conference_Location :
San Diego, CA
Type :
conf
DOI :
10.1109/SMC.2014.6973961
Filename :
6973961
Link To Document :
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