中文摘要：

在这个工作，图象特征向量为包含足够的信息的块被形成，它用一个单个值的标准被选择。当在开始的二 SV 之间的比率在给定的阀值下面时，块被认为增进知识。包括亮度，颜色部件和质地措施的统计的 12 个特征的一个总数被用来形成中间的向量。主要部件分析然后被执行把尺寸归结为 6 给最后的特征向量。构造特征向量的关联被聚类的 k 工具在被用来因此组织向量的实验表明块。掉进一样的组的块显示出类似的视觉外观。

英文摘要：

In this work, image feature vectors are formed for blocks containing sufficient information, which are selected using a singular-value criterion. When the ratio between the first two SVs axe below a given threshold, the block is considered informative. A total of 12 features including statistics of brightness, color components and texture measures are used to form intermediate vectors. Principal component analysis is then performed to reduce the dimension to 6 to give the final feature vectors. Relevance of the constructed feature vectors is demonstrated by experiments in which k-means clustering is used to group the vectors hence the blocks. Blocks falling into the same group show similar visual appearances.