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中文摘要：
分析了图像的颜色空间模型，以HSI为基础模型，对采集到的瓜果图像进行去噪、分割、边缘提取等预处理。在此基础上，对水果图像的特征以及相关参数进行测量，最后采用BP神经网络及K-近邻规则对目标进行识别。实验证明，BP算法的识别率较高，系统总体识别率达到了98．92％，完全达到了应用需求。
英文摘要：
The color space model is analyzed in this paper. Based on HSI model, the pretreatment methods includes fruit image noise removing, segmentation, and edge extraction were done. Then the features and parameters were measured. At last we use BP neural network and K - Nearest Neighbor （KNN） rules to recognize the goal. The experimentation indicates that the recognition percent of BP neural network is very high. The recognition rate is about 98.92 percent, which reaches the application requirements.
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Two-dimensional local graph embedding discriminant analysis (2DLGEDA) with its application to face a
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