Title :
Real-time range image segmentation on GPU
Author :
Jin Xin Hua ; Mun-Ho Jeong
Author_Institution :
Dept. of Control & Instrum. Eng., Kwangwoon Univ., Seoul, South Korea
Abstract :
In this paper propose 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.
Keywords :
graphics processing units; image segmentation; neural nets; parallel processing; real-time systems; 8-neiborhood oscillators; GPU-based parallel processing method; LEGION; edge-based categories; locally excitatory globally inhibitory oscillator networks; neural oscillator network; real-time range image segmentation method; region-based categories; Graphics processing units; HTML; Image edge detection; Image segmentation; Indexes; Integrated circuits; Oscillators; CUDA; GPGPU; LEGION; range image segmentation;
Conference_Titel :
Control, Automation and Systems (ICCAS), 2014 14th International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-8-9932-1506-9
DOI :
10.1109/ICCAS.2014.6987976