DocumentCode
1768780
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
fYear
2014
fDate
22-25 Oct. 2014
Firstpage
150
Lastpage
153
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Automation and Systems (ICCAS), 2014 14th International Conference on
Conference_Location
Seoul
ISSN
2093-7121
Print_ISBN
978-8-9932-1506-9
Type
conf
DOI
10.1109/ICCAS.2014.6987976
Filename
6987976
Link To Document