Abstract
This paper describes a method to know objects in outdoor environment for autonomous robot navigation. The proposition of the method segments and recognizes the object from an image taken by moving robot in outdoor environment. Features are color, straight line, edge, HCM (Hue Co-occurrence Matrix), PCs (Principal Components), vanishing point and geometrical information. We classify the object natural and artificial. We detect tree of natural object and building of artificial object.Then we define their characteristics individually. In the process, we segment regions objects included by preprocessing. Objects can be recognized when we combine predefined multiple features. The correct object recognition of proposed system is over 92% among our test database which consist about 1200 images. We confirm the result of image segmentation using multiple features and object recognition through experiments.
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Kim, DN., Trinh, HH., Jo, KH. (2007). Object Recognition of Outdoor Environment by Segmented Regions for Robot Navigation. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues. ICIC 2007. Lecture Notes in Computer Science, vol 4681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74171-8_121
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DOI: https://doi.org/10.1007/978-3-540-74171-8_121
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74170-1
Online ISBN: 978-3-540-74171-8
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