This paper researched on the fuzzy and gray theory, recognized facial image by fuzzy and gray method, which can reduce original data and guarantee and improve the precision.
本文通过对模糊灰色理论的研究，利用模糊灰色理论方法对人脸图像进行识别，可以减少所需原始数据，保证并提高识别精度。
Without considering the spatial information of images, the original fuzzy C-means algorithm is very sensitive to image noise.
由于原始的模糊c -均值聚类算法没有考虑图像的空间信息，算法对图像中的噪音点十分敏感。
In the application of the image segmentation, the new model solves the over-segmentation of the original Fuzzy ART neural network algorithm due to the vigilance's increase.
将该模型应用于图像分割，解决了传统模糊art网络图像分割结果随警戒参数的升高而出现的过度分割。
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