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The Research of Mixed Programming Auto-Focus Based on Image Processing

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Information Computing and Applications (ICICA 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 105))

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Abstract

Auto-focus technology is an important way to improve the accuracy of indentation diameter measurement system, intelligent and automate. This article describes the use of image processing method to achieve the auto-focus technologies of indentation diameter measurement system, at its core is to choose an appropriate image clarity evaluation function. After studying a number of image clarity evaluation functions is proposed the image clarity evaluation function which based on the vector mode and improved DCT transform. Experiments show that the proposed algorithm has a good unimodality, accuracy, stability, reliability and rapidity. Finally using COM Component Technology-based Matlab and VB mixed programming to ensure that algorithms and software can be design.

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References

  1. Zi-fu, W., Du-yan, I., Jian-jun, U.: An Qin-bo: Ensemble Contour Traking. Opto-Electronic Engineering 37(5), 12–18 (2010)

    Google Scholar 

  2. Yu-lan, L., Hai-qi, Z., Ping, W., Rui-hong, Y., Li-wei, T., Jun-ying, L.: Gun Bore Flaw Image Recognition Based on Power-amplitude Spectrum. Opto-Electronic Engineering 37(5), 36–40 (2010)

    Google Scholar 

  3. Chuan-bin, Z., Zheng-long, D.: Study on Wavelet Filtering for Signal of Ring Laser Gyro. ACTA Electronica Sinica 32(1), 125–127 (2004)

    Google Scholar 

  4. Wornell, G.W., Oppenhein, A.V.: Estimation of Signals from Noisy Measurements Using Wavelets. IEEE Transactions on Signal Processing 40(3), 611–623 (1992)

    Article  Google Scholar 

  5. Mallat, S.: A Wavelet Tour of Signal Processing. China Machine Press, Beijing (2002)

    MATH  Google Scholar 

  6. Fu-ming, F., Liang-lun, C., Xiao-fen, W., Jian-hua, P.: A new type of high-speed automatic focusing system. Opto-Electronic Engineering 37(5), 127–132 (2010)

    Google Scholar 

  7. Zhi-cheng, Z., Zhi-yuan, L., Jing-gang, Z.: Robust IMC-PID controller design for an opto-electronic tracking system with time-delay. Opto-Electronic Engineering 37(1), 30–36 (2010)

    Google Scholar 

  8. Zhi-hai, S., Wan-zeng, K., Shan-an, Z.: Scale and direction adaptive locating of video moving objects with subtractive clustering. Opto-Electronic Engineering 37(1), 37–42 (2010)

    Google Scholar 

  9. Chou, K.C., Golden, S.A., Willsky, A.S.: Multiresolution Stochastic Models, Data Fusion, and Wavelet Transform. Signal Processing 34(3), 257–282 (1993)

    Article  MATH  Google Scholar 

  10. Craigmile, P.F., Guttorp, P., Percival, D.B.: Wavelet-Based Parameter Estimation for Trend Contaminated Fractionally Di-erenced Processes, Technical Report Series NRCSE-TRS No. 077 February 4, 1-30 (2004)

    Google Scholar 

  11. Deriche, M., Tewfik, A.H.: Maximum Likelihood Estimation of the Parameters of Discrete Fractionally Differenced Gaussian Noise Process. IEEE Trans. on Signal Processing 41(10), 2977–2989 (1993)

    Article  MATH  Google Scholar 

  12. Hirchoren, G.A., Attellis, C.E.D.: Estimation of Fractal Signals Using Wavelets and Filter Banks. IEEE Trans. on Signal Processing 46(6), 1624–1630 (1998)

    Article  Google Scholar 

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Zhang, S. et al. (2010). The Research of Mixed Programming Auto-Focus Based on Image Processing. In: Zhu, R., Zhang, Y., Liu, B., Liu, C. (eds) Information Computing and Applications. ICICA 2010. Communications in Computer and Information Science, vol 105. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16336-4_29

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  • DOI: https://doi.org/10.1007/978-3-642-16336-4_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16335-7

  • Online ISBN: 978-3-642-16336-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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