Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Robust analysis of feature spaces: color image segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
A New Method of Color Image Segmentation Based on Intensity and Hue Clustering
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
Localization Based on Building Recognition
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Nonlinear color space and spatiotemporal MRF for hierarchical segmentation of face features in video
IEEE Transactions on Image Processing
Object analysis for outdoor environment perception using multiple features
ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
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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.