A novel method of content-based image segmentation using deformable template matching is proposed.A two-dimensional (2-D) deformable template based on orthogonal curves is built by pre-computing extensions of the deformable template along orthogonal curve
A novel method of content-based image segmentation using deformable template matching is proposed.A two-dimensional (2-D) deformable template based on orthogonal curves is built by pre-computing extensions of the deformable template along orthogonal curve
本文提出一种采用可变形模板匹配技术进行基于内容的图像分割算法.通过预先计算出可变形模板沿着变形的正交曲线，并对模板曲线及正交曲线进行离散抽样，建立一基于正交曲线的二维(2-D)可变形模板，针对图像分割问题定义控制可变形模板进行变形的内、外部能量函数，本文采用遗传算法搜索能量函数最小的全局最优解.该新算法比传统的可变形模板匹配方法降低了搜索空间的维数，减少了算法对模板初始位置的敏感.对实际图像及模拟低信噪比图像处理的结果表明，新算法具有良好的分割精度及稳定性.