Due to the large number of feature values which can be extracted from wavelet moment, a discrete invasive weed optimization algorithm is proposed to select the feature vectors with between-class scatter matrix and within-class scatter matrix, and finally can recognize images with the help of BP neural network as the classifier. The simulation results show that, compared to the feature selection algorithm, the improved discrete invasive weed optimization algorithm has the shorter selection time of image feat...
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