Abstract
Nowadays we are surrounded by colorful images and image processing has become an important subject. We have to carry on all kinds of implementations such as image classification, image recognition, image searching and so on. However, direct operation to those images is difficult because of the features -- nonlinear, high dimensionality, large quantity. To reduce the dimensionality and remain original features, people created many algorithms such as PCA, MCS and ANN. In this paper, I introduce one dimensionality reduction called locally linear embedding (LLE), which is created by Sam and Lawrence. The LLE algorithm is one nonlinear dimensionality reduction method. I make use of the LLE algorithm to do an experiment of face recognition. By the LLE algorithm I reduce the 92*112-dimension-image to 6 dimensions and successful recognize the face image.
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