k-NN Classification of handwritten characters using a new distortion-tolerant matching measure
k-NN Classification of handwritten characters using a new distortion-tolerant matching measure
复制标题
使用新的失真容忍匹配方法对手写字符进行 k-NN 分类
DOI：
10.1109/icpr.2014.54
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Yukihiko Yamashita and Toru Wakahara
中科院分区：
文献类型：
--
作者：
Yoshikazu Washizawa;Tatsuya Yokota;and Yukihiko Yamashita;Yukihiko Yamashita and Toru Wakahara;Yukihiko Yamashita and Toru Wakahara
Wakahara等人提出的全局仿射变换（GAT）相关方法。是一种模式匹配方法，可以补偿嵌入在输入模式中的仿射变换。 GAT相关方法在字符识别和对象匹配方面表现出高性能。例如，在IPTP手写数字数据库上进行的字符识别实验中，它优于众所周知的切线距离（TD）方法。本文的目的有三个。首先，我们结合 GAT 相关方法引入了一种新的匹配度量，称为等梯度方向的最近邻距离（NNDEGD）。 NNDEGD就是GAT相关方法中使用的高斯函数的窗口参数，它等于一幅图像中的一个点与另一幅图像中具有相同梯度方向的另一个点之间的平均最小距离。我们建议使用该值作为新的匹配度量。其次，我们扩展了GAT相关方法，以便在仿射变换之外处理笔画宽度的变化。最后，我们将 GAT 相关方法的原始版本和扩展版本应用于使用 MNIST 数据库的 fc-NN 分类实验。这些实验首次高效地进行，因为我们大大降低了原始 GAT 相关方法中涉及的计算复杂度和内存负载。我们成功地证明，与竞争的失真容忍模板匹配技术相比，增强型 GAT 相关方法实现了 0.49% 的最低错误率。
The global affine transformation (GAT) correlation method proposed by Wakahara et al. is a pattern matching method that can compensate for affine transformation embedded in an input pattern. The GAT correlation method demonstrated a high performance in character recognition and object matching. For example, it outperformed the well-known tangent distance (TD) method in character recognition experiments made on IPTP handwritten numeral database. The purpose of this paper is threefold. First, we introduce a new matching measure called the nearest neighbor distance of equi-gradient direction (NNDEGD) in cooperation with the GAT correlation method. The NNDEGD is just the window parameter of the Gaussian function used in the GAT correlation method, which is equal to the average minimum distance between a point in one image and another point in the other image with the same gradient direction. We propose to use this value as a new matching measure. Secondly, we extend the GAT correlation method so as to handle the change of stroke width besides the affine transformation. Finally, we apply the original and extended versions of the GAT correlation method to fc-NN classification experiments using the MNIST database. These experiments are carried out efficiently for the first time because we have substantially reduced the computational complexity and memory load involved in the original GAT correlation method. We successfully show that the enhanced GAT correlation method has achieved the lowest error rate of 0.49% compared with competing distortion-tolerant template matching techniques.