JSIP  Vol.4 No.3 B , August 2013
Image Processing Techniques in Shockwave Detection and Modeling
Abstract: Shockwave detection is critical in analyzing shockwave structure and location. High speed video imaging systems are commonly used to obtain image frames during shockwave control experiments. Image edge detection algorithms become natural choices in detecting shockwaves. In this paper, a computer software system designed for shockwave detection is introduced. Different image edge detection algorithms, including Roberts, Prewitt, Sobel, Canny, and Laplacian of Gaussian, are implemented and can be chosen by the users to easily and accurately detect the shockwaves. Experimental results show that the system meets the design requirements and can accurately detect shockwave for further analysis and applications.
Cite this paper: S. Cui, Y. Wang, X. Qian and Z. Deng, "Image Processing Techniques in Shockwave Detection and Modeling," Journal of Signal and Information Processing, Vol. 4 No. 3, 2013, pp. 109-113. doi: 10.4236/jsip.2013.43B019.

[1]   L. G. Roberts, “Machine Perception of Three-Dimensional Solids,” Optical and Electro-Optical Information Processing, J. T. Tippett, et al., Eds., May 1965.*

[2]   J. M. S. Prewitt, “Object enhancement and extraction,” Picture Processing and Psychopictorics, B. Lipkin and A. Rosenfeld, Eds., New York: Academic Press, 1970, pp. 75-149.

[3]   I. E. Sobel, “Camera Models and Machine Perception,” Stanford Doctoral Dissertation, 1970.

[4]   J. Canny, “A Computational Approach to Edge Detection,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-8, No. 6, 1986, pp. 679-698. doi:10.1109/TPAMI.1986.4767851

[5]   D. C. Marr and E. Hildreth, “Theory of Edge Detection,” in Proceedings of the Royal Society of London, Vol. 207, No. 1167, Feb. 1980, pp. 187-217. doi:10.1098/rspb.1980.0020