关键词: 图像识别, 特征选择, 小波矩, 入侵性杂草优化算法

Abstract: 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 feature vectors, the higher accuracy, and can effectively improve the performance of the classifier.

Key words: image recognition, features selection, wavelet moment, invasive weed optimization algorithm