Object Recognition using Segmented Region and Multiple Features on Outdoor Environments
Dae-Nyeon Kim, Hyun-Deok Kang, Taeho Kim, Kang-Hyun Jo
- 发表年份
- 2006
- 引用次数
- 3
摘要
This paper presents the method of region segmentation like six features, color, edge, straight line, geometric information, and template of tree color. The proposition of method segments region of image which is obtained by CCD camera mounted on the mobile robot. Moving robot takes database images on outdoor environment. We classify object to natural and artificial and then define their characteristics individually. In the process, we segment regions included objects by preprocessing. Objects can be recognized when we combine predefined multiple features. In addition, the feature of XCM (X co-occurrence matrix) detect region of tree, where X is information of arbitrary like intensity or hue. So the features use XCM as well as five features which we define. Our method is more effective than conventional region segmentation on outdoor environment because we present the method to combine various features in complex image. We achieved the result of region segmentation using multiple features through experiments.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991