图像元 meaning in Chinese
image primitive
Examples
- How to : read image metadata
如何：读取图像元数据 - In this paper , we first established the image metadata used in our system which based on the famous dublin core , then we analyzed the abstraction and description visual features of image such as color texture and shape . next , we discussed the problem of similarity measure of visual feature , imported fuzzy logic into the distance feature and pointed out the disadvantages of geometry space based methods . for multi - dimension vector ' s high dimension nature , it ' s hard to index with traditional methods , we discussed how to lower the dimension using clustering and klt transformation
本文首先在dublincore的基础上制定了适合我们要求的图像元数据集；详细分析了颜色、纹理、形状等视觉特征的提取和表示方法；探讨了图像视觉特征相似度量的问题，将模糊技术引入直方图的距离度量，分析了几何空间距离度量函数的不足之处，提出了系统中采用的距离函数；针对图像视觉特征向量的多维特性，分析了现有的各种降维技术和多维索引技术。 - Based on the international general metadata standard dublin core , we first established the military image metadata , and then analyzed the extraction and description of the visual features such as color , texture and shape . next we discussed the similarity measurements of visual features , imported fuzzy logic into the distance feature , compared correlative performances , pointed out the disadvantages of space - based geometry functions , and brought forward a distance function . for multi - dimension vector ' s high dimension nature , we probed into the existing dimension - lowering technology and multi - dimension index technology , and selected the most suitable method to establish multi - dimension index in our system
首先在国际通用的元数据标准dublincore的基础上制定了适合军队要求的图像元数据集，并详细分析了颜色、纹理、形状等视觉特征的提取和表示方法；接着探讨了图像视觉特征相似度量的问题，将模糊技术引入到颜色直方图的距离度量中并进行了相关性能的分析比较，指出了几何空间距离度量函数的不足之处，改进了系统中采用的距离函数；然后针对图像视觉特征向量的多维特性，分析了现有的各种降维技术和多维索引技术。