Abstract
With the development of graphic and image processing technology, strong convective weather of Zhaoqing city subarea monitoring and early-warning system (ZQMES) is developed. It uses region growing and arc-length methods to process weather radar image. The specified intensity radar echo is extracted, and the map of Zhaoqing is drawn. The radar echo image and the map are overlapped. The principle of judging whether a strong echo existed in a certain town is judging whether a pixel point of the radar echo image existed in a polygon area of the Zhaoqing map. The system can judge automatically which areas was affected by strong convective echo by using improved arc-length method. As an example, the development of the system provides the experimental basis for the study on region growing and arc-length methods.
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Huang, T., Jiao, F.: Data transfer and extension for mining big meteorological data. In: Huang, D.-S., Bevilacqua, V., Premaratne, P., Gupta, P. (eds.) ICIC 2017. LNCS, vol. 10361, pp. 57–66. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-63309-1_6
Hwang, Y.I., Paek, I., Yoon, K., Lee, W., Yoo, N., Nam, Y.: Application of wind data from automated weather stations to wind resources estimation in Korea. J. Mech. Sci. Technol. 24, 2017–2023 (2010). https://doi.org/10.1007/s12206-010-0613-z
Wang, X., Jin, X.M., Chen, M.G., Zhang, K., Shen, D.: Topic mining over asynchronous text sequences. IEEE Trans. Knowl. Data Eng. 24(1), 156–169 (2012)
Shen, P.Y., Luo, Y.Z.: Application of electronic sand table system in geological disasters meteorological service based on GIS. Meteorol. Environ. Res. 5(2), 66–69 (2014)
Cremonini, R., Tiranti, D., Barbero, S.: The urban flooding early warning system of the greater turin (North-Western Italy) based on weather-radar observations. Eng. Geol. Soc. Territory 5, 837–842 (2015)
Wan, C., Jin, X.M., Ding, G.G., Shen, D.: Gaussian cardinality restricted boltzmann machines. In: Twenty-ninth AAAI Conference on Artificial Intelligence, pp. 3031–3037 (2015)
Guo, Y.C., Ding, G.G., Jin, X.M., Wang, J.M.: Learning predictable and discriminative attributes for visual recognition. In: Proceedings of 29th AAAI Conf. on Artificial Intelligence (AAAI) (2015)
Otsu, N.: A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. 9, 62–66 (1979). https://doi.org/10.1109/TSMC.1979.4310076
Schulz, D., Burgard, W., Fox, D., Cremers, A.B.: Tracking multiple moving targets with a mobile robot using particle filters and statistical data association. IEEE Int. Conf. Robot. Autom. 2, 1665–1670 (2001)
Mallat, S., Zhong, S.: Characterization of signals from multiscale edges. IEEE Trans. Pattern Anal. Mach. Intell. 7, 710–732 (1992)
Zhu, Q.D., Jing, L., Bi, R.: Exploration and improvement of Ostu threshold segmentation algorithm. In: 2010 8th World Congress on Intelligent Control and Automation (WCICA), pp. 6183–6188 (2010)
Giuliano, A., Michele, C.: Microarray image gridding with stochastic search based approaches. Image Vis. Comput. 25(2), 155–163 (2007)
Shih, F.Y., Cheng, S.: Automatic seeded region growing for color image segmentation. Image Vis. Comput. 23, 877–886 (2005)
Fu, Z., Yang, Y., Shu, C., Li, Y., Wu, H., Xu, J.: Improved single image dehazing using dark channel prior. Syst. Eng. Electron. Technol. 26(5), 1070–1079 (2015)
Wang, X.Y., Bu, J.: A fast and robust image segmentation using FCM with spatial information. Digit. Signal Process. 20(4), 1173–1182 (2010)
Acknowledgments
The authors were supported by Science and technology innovation project of Zhaoqing (Grant No. 201624030904), Science and technology research project of Guangdong Meteorological Bureau (Grant No. 2016B51), Science and technology research project of Zhaoqing Meteorological Bureau (Grant No. 201609, No. 201708), Intelligent gridded forecasting team of Guangdong Meteorological Bureau (No. 201706).
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Jiao, F., Huang, T., Zhou, Y. (2018). Study on Image Processing Based on Region Growing and Arc-Length Methods. In: Huang, DS., Bevilacqua, V., Premaratne, P., Gupta, P. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science(), vol 10954. Springer, Cham. https://doi.org/10.1007/978-3-319-95930-6_34
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