Wood species identification using feature-level fusion scheme |
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Authors: | Peng Zhao Gang Dou Guang-Sheng Chen |
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Institution: | 1. Information and Computer Engineering College, Northeast Forestry University, Harbin City, 150040, China;2. College of Photo-electronic Engineering, Beijing Institute of Technology, Beijing City 100081, China |
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Abstract: | In this paper, we propose a robust wood species identification scheme by using a feature-level fusion scheme. First, a novel wood feature acquirement system is devised, which can get the curve of 1D wood spectral reflectance ratio and the 2D wood surface color image. Second, the 4 wood color features, the 4 principal texture features, the 4 secondary texture features and the 4 spectral features are established, respectively. Third, a fuzzy BP neural network is proposed to perform the classification work, which consists of 4 sub-networks based on the color feature, texture feature and spectral feature. We have experimentally proved that this scheme improves the mean recognition accuracy to approximately 90% for 5 wood species. Moreover, our feature-level fusion scheme is superior to the recognition schemes which use color feature and texture feature. |
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Keywords: | Wood species identification Image processing Color Texture Spectral analysis |
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