基于二维阈值向量分割的足迹边缘提取方法

根据足迹图像特点,提出了基于灰度 梯度二维阈值向量区域分割的边缘提取方法·该方法以灰度 梯度共生矩阵为模型,利用最大熵原理,自动求出灰度 梯度二维阈值向量;用此二维阈值向量对图像进行区域分割,具有抗干扰能力强和正确分割模糊边缘像素的特点,构造两个适合足迹图像特点的结构元算子,对区域分割后的二值图像作数学形态学运算,以光滑边缘、提取边缘·大量实验表明,用本文方法提取的足迹边缘光滑,与原始图像具有很高的相似性;噪声得到抑制,取得令人满意的效果·

Approach to Extracting Footprint Edge Using 2D Threshold Vectors

The geometrical feature of the edge of human footprint contains lots of human body information, but it is of great significance to extract exactly the edge of footprint. According to the characteristics of footprint image, an approach to extracting footprint edge is presented on the basis of the segmentation of the image area of 2-dimensional gray level-gradient threshold vector. The 2-dimensional threshold vectors can be computed automatically, based on the gray level-gradient cooccurrent matrix model and maximum entropy theory. This method can segment the images by using auto-developed 2-dimensional gray level-gradient threshold vectors, and acquire high anti-noise capacity and high accuracy of segmentation of the fuzzy edge pixies as well. To extract and smooth the footprint edge, 2 structural operators are set up to adopt to the feature of footprint images, with the segmented images computed through a morphologic method. The satisfactory test results show that the footprint edges extracted in this way are of high similarity to original ones with noise suppressed.