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一种保形的快速图象形态细化算法

盛业华1, 唐 宏1, 杜培军1, 郭达志1(中国矿业大学测绘与空间信息工程研究所,徐州 221008)

摘 要
骨架是一种重要的图象目标几何特征.对不同形状的图象目标,如何快速地获得其非畸变骨架,是进行图象目标的形状分析、特征提取、模式识别等应用的前提.基于数字形态学的形态细化是获取图象目标骨架的有效细化方法之一.它采用具有一定形状的预定义结构元素,对图象进行形态薄化运算,仅需进行移位和逻辑运算就能完成.但是形态细化一般使用序贯细化算法,在每次细化迭代过程中,只能采用单一的结构元素对目标进行薄化,因此存在着收敛速度慢、易产生畸变骨架等缺点.本文提出的保形快速形态细化算法在细化迭代过程,每次迭代同时使用4种不同方向的同伦结构元素与目标进行击中运算,并以击中运算结果的并集作为象素是否剥落的依据,使得目标能从各方向快速、均匀地收敛至其骨架.对不同字体的汉字图象的实验结果表明,这一算法能产生均匀、整齐、畸变小的汉字骨架,且其运行速度比序贯形态细化方法快4倍以上.
关键词
One Fast Shape Preserving Morphological Thinning Algorithm

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Abstract
Skeleton is a kind of important geometric characteristic of image. How to fast acquire the non-distorted skeleton of image with different shape and size is the precondition for those applications such as shape analysis, characteristic extraction or pattern recognition. Morphologic thinning algorithms based on mathematical morphology are effective thinning approaches to obtaining skeletons of image, which use some pre-defined structure elements with definite shape to operate on the image, only some shifting and logical operations are needed. But the traditional sequential morphological thinning algorithm has the disadvantage that its convergence speed is too slow and using only one structure element to carry out the thinning in every interation may produce distorted skeletons. A new thinning algorithm named fast shape preserving morphological thinning algorithm is advanced in this paper. The algorithm uses four types of structure elements of different direction simultaneously to operate on the image with the hitting operation. The union set of the hitting result is taken as the foundation of whether the outer pixels are exfoliated, thus it can cause the image to converge to its skeleton in every direction fast and symmetrically. The test result of an image of Chinese characters with various fonts enunciates that this algorithm can obtain symmetrical, regular and non-distorted skeletons of the Chinese characters, and its convergent speed is four times more than the speed of sequental morphological thinning algorithm.
Keywords

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