Image Feature Attributes Reduction Based on PCA Pre-processing
基于PCA预处理的图像特征属性约简

The paper discusses the application of Principle Component Analysis(PCA) in image's feature attributes reduction.After PCA pre-processing,Rough Set theory was introduced,and its application in characterized parameters' attribute optimization was also explored.The unnecessary attributes were eliminated with an attribute reduction algorithm.The inner redundancy of CBIR was revealed.The result of attribute reduction using UCI dataset proved the algorithm can exclude the influence of unused attributes and decrease the complexity of CBIR effectively.