关键词: k最近邻算法（kNN）, 人脸识别, 文字识别, 医学图像处理

Abstract: K nearest neighbor（kNN） algorithm is a simple classification algorithm, the algorithm consists of two steps： （1）Find out a set of k on a given search training set measure at a distance. （2）The classification is according to the most consistent classes in this kNN algorithm. The non-parametric property of kNN algorithm makes it very easy to implement, and its classification error is restricted by two times of the Bayes error. Therefore, the kNN algorithm is still the most popular choice for pattern classification. This paper summarizes many literatures by using kNN algorithm, expounding the improvement methods used in each document, and analyzing the experimental results. By analyzing the kNN algorithm in face recognition, text recognition, medical image-processing and other applications achieved good classification results, this paper is very promising for the development of kNN algorithm.

Key words: k-Nearest-Neighbors（kNN） algorithm, face recognition, text recognition, medical image processing