Abstract
Image feature extraction is crucial in image target recognition. This paper presents a method of image feature extraction by combining wavelet decomposition. The image is first decomposed by wavelet transforms, and the decomposed coefficients are reconstructed to form a new time series, from which some energy vector can be extracted by time-frequency domain analysis. By calculating correlation coefficients, it is possible to recognize whether target signal is involved or not in gained image. The effectiveness of the method is verified by a real image with additive simulated noise signal, especially under the condition of low SNR.
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© 2009 Springer-Verlag Berlin Heidelberg
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Zhao, M., Chai, Q., Zhang, S. (2009). A Method of Image Feature Extraction Using Wavelet Transforms. In: Huang, DS., Jo, KH., Lee, HH., Kang, HJ., Bevilacqua, V. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2009. Lecture Notes in Computer Science, vol 5754. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04070-2_21
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DOI: https://doi.org/10.1007/978-3-642-04070-2_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04069-6
Online ISBN: 978-3-642-04070-2
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