摘要
提出了一种新的计算特征图像的主成分分析方法,该方法被称为图像分块算法。在此方法中,目标被表示为特征和它们相对位置(称为拓扑)的集合,这是一种局部和全局算法。当把这种方法用于解决遮挡问题时,可以发现这种方法得到的图像表示效果比传统的主成分分析方法得到的图像表示效果更好。同时,一种基于这个新的图像表示的简单图像识别算法也被提出,并进行了大量实验。实验表明,这种新方法对于带有53%遮挡部分的图像仍然有95%以上的识别率。
A new method to compute eigenimages in principal component analysis(PCA) based vision systems is presented.It is called the mosaic image method.In this method,the object is represented as a collection of features and their relative positions(topology).This is a local and global method.Although this method is created to account for the occlusion problem,it is found that the resulting representation is better than that obtained using the traditional optimum representation.A simple algorithm for recognition based on the new representation is proposed.Extensive experiments are conducted.It is found that the new method can accommodate up to 53% occluded parts with a recognition rate of more than 95%.
出处
《电脑知识与技术》
2013年第1X期586-589,共4页
Computer Knowledge and Technology
基金
三亚市院地科技合作项目(2011YD36)
