Abstract
In this paper, we proposed a classified strategy on borehole images of logging interpretation. According to the visualized characteristics of borehole images, the analysis of texture is the main objective of this paper. Local Binary pattern (LBP) histogram is adopted to capture the texture information that will be defined as low level textures. Then dominant features of a certain kind will be figured out among low level textures. Finally, after arrangement combination of these dominant features, appropriate meta feature will be presented. The meta feature is a certain kind of feature structure that used as input vectors for classifier.
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References
Wang, F., Wen, Z.F., Zhong, J.H., Li, Y., Wang, H.Q.: Logging response and interpretation on reef in Western Qaidam Basin, vol. 29(2), pp. 133–136. Well Logging Technology, China (2005)
Goyal, R.K., Goh, W.L., Mital, D.P., Chan, K.L.: Invariant element compactness for texture classification. In: Proceedings of the Third International Conference on Automation, Robotics and Computer Vision (1994)
Zhang, J., Tan, T.: Brief review of invariant texture analysis methods. Pattern Recognition 35, 735–747 (2002)
Carlos, A.-C., Risto, R.-K., Mario, R.-A., Andrade-Gonzalez, A., Rafael, E.-P.: High-order statistical texture analysis-—font recognition applied. Pattern Recognition Letters 26(2) (January 15, 2005)
Julesz, B.: Experiments in the visual perception of texture. Sci. Am. 232, 34–43 (1975)
Kohonen, T., Hynninen, J., Kangas, J., Laaksonen, J.: Lvqpak: A software package for the correct application of learning vector quantization algorithms (1992), http://ieeexplore.ieee.org
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Fan, C., Wang, H. (2012). Classification Model Analysis of Logging Image Based on Metafeatures. In: Zhang, Y. (eds) Future Wireless Networks and Information Systems. Lecture Notes in Electrical Engineering, vol 143. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27323-0_4
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DOI: https://doi.org/10.1007/978-3-642-27323-0_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27322-3
Online ISBN: 978-3-642-27323-0
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