One class classification is a machine learning approach different from the traditional pattern recognition approach where two or more class samples are required . however in some real-life cases, we can hardly, even not, get the samples of some classes, or have to pay costly price to obtain the so-needed samples, such as in the case of machinery malfunction . and while in other cases, the sizes of samples among classes are imbalance, such as medical diagnosis 单类分类器是不同于传统模式识别的一种机器学习方法,传统模式识别方法一般需要多个类别的样本(至少两个),而在有些场合中,几乎无法获取多类的样本,或者获取其样本所需花费的代价非常高,比如:机器故障中我们不可能为了去获得故障样本而让机器特意产生故障;又有些场合的类别样本个数严重不平衡,比如医学上的疾病特征与非疾病特征的比例是严重不平衡的。
This paper is concerned with the popular texture analysis technique in the traditional image recognition, the novel pattern recognition approach, namely synergetic neural network pattern recognition, and their applications . furthermore, it proposes and implements an offline handwriting identification multi-classifier . it is organized as follows 本论文研究了传统图像识别方法中常用的纹理分析法及一种新的模式识别方法??协同神经网络模式识别法及其应用,并在此基础上构造了一个离线手写体笔迹鉴别多分类器模型。