Title :
Particle Tracking Velocimetry Using Cellular Neural Network
Author :
Ohmi, Kazuo ; Sapkota, Achyut
Author_Institution :
Osaka Sangyo Univ., Osaka
Abstract :
Recent advances in digital image processing techniques, electronic and optical hardware have facilitated the investigation of fluid mechanics among the others. Flow visualization is the indispensable tool in the investigation of complex flow structures. The present study is focused in the development of an algorithm for particle tracking velocimetry (PTV), a powerful flow visualization tool, using cellular neural network. Significant improvement in computation time has been achieved with the proposed algorithm citing comfortable way to the use of neural network in flow visualization which was previously seemed tedious due to long computation time.
Keywords :
cellular neural nets; computational fluid dynamics; particle track visualisation; velocity measurement; cellular neural network; flow visualization; particle tracking velocimetry; Cellular neural networks; Data mining; Digital images; High speed optical techniques; Image motion analysis; Optical films; Optical sensors; Particle tracking; Velocity measurement; Visualization;
Conference_Titel :
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9490-9
DOI :
10.1109/IJCNN.2006.246917