Authors:
Sung Woo Yang
;
Ihn Cheol Kim
and
Jin Soo Kim
Affiliation:
3-1-2, Agency for Defense Development, Korea, Republic of
Keyword(s):
Skyline extraction, mountainous images, canny edge images, skyline candidate pixel.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Feature Extraction
;
Features Extraction
;
Image and Video Analysis
;
Informatics in Control, Automation and Robotics
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
Skyline extraction in mountainous images which has been used for navigation of vehicles or micro unmanned air vehicles is very hard to implement because of the complexity of skyline shapes, occlusions by environments, difficulties to detect precise edges and noises in an image. In spite of these difficulties, skyline extraction is a very important theme that can be applied to the various fields of unmanned vehicles applications. In this paper, we developed a robust skyline extraction algorithm using two-scale canny edge images, topological information and location of the skyline in an image. Two-scale canny edge images are composed of High Scale Canny edge image that satisfies good localization criterion and Low Scale Canny edge image that satisfies good detection criterion. By applying each image to the proper steps of the algorithm, we could obtain good performance to extract skyline in images under complex environments. The performance of the proposed algorithm is proved by experi
mental results using various images and compared with an existing method.
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