论文标题
图像和纹理分类的2-D签名
2-d signature of images and texture classification
论文作者
论文摘要
我们为图像引入了适当的二维签名概念。该对象的灵感来自所谓的粗糙路径理论，并捕获了二维对象（例如图像）的许多基本特征。因此，它是用于模式分类的低维特征。在这里，我们实施一个简单的过程来进行纹理分类。在这种情况下，我们表明，基于签名的低维功能集可产生极好的精度。
We introduce a proper notion of 2-dimensional signature for images. This object is inspired by the so-called rough paths theory, and it captures many essential features of a 2-dimensional object such as an image. It thus serves as a low-dimensional feature for pattern classification. Here we implement a simple procedure for texture classification. In this context, we show that a low dimensional set of features based on signatures produces an excellent accuracy.
