GPU-Based Real-Time Range Image Segmentation

被引:0
|
作者
Jin, Xinhua [1 ]
Kang, Dong Joong [2 ]
Jeong, Mun-Ho [1 ]
机构
[1] Kwangwoon Univ Seoul, Intelligence Lab, Seoul, South Korea
[2] Pusan Natl Univ, Dept Engn Mech, Seoul, South Korea
来源
关键词
Range image segmentation; CUDA; LEGION; GPGPU;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper proposed a GPU-based parallel processing method for real-time image segmentation with neural oscillator network. Range image segmentation methods can be divided into two categories: edge-based and region-based. Edge-base method is sensitive to noise and region-based method is hard to extracting the boundary detail between the object. However, by using LEGION (Locally Excitatory Globally Inhibitory oscillator networks) to do range image segmentation can overcome above disadvantages. The reason why LEGION is suitable for parallel processing that each oscillator calculate with its 8-neiborhood oscillators in real time when we process image segmentation by LEGION. Thus, using GPU-based parallel processing with LEGION can improve the speed to realize real-time image segmentation.
引用
收藏
页码:293 / 297
页数:5
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