摘要
基于传统指纹图像分割算法,提出一种改进的Mean Shift指纹图像分割算法.该算法利用指纹图像固有的方向性特性,把经过分割后的每个指纹图像区域抽象为一个样本点,将区域内像素点的灰度均值作为均值向量,从而有效地实现了指纹图像分割.实验结果表明,该算法能准确地将指纹图像中的模糊区域和背景区域分离,提高了指纹图像分割的精确度,并且对于多数指纹图像准确性较好.
After analysis and research on the traditional fingerprint image segmentation algorithm, an improved Mean Shift algorithm for fingerprint image segmentation was introduced. The algorithm makes fully use of the inherent directional characteristics of fingerprint image to abstract each area of fingerprint image after segmen- ting into a sample point and to consider the grayscale mean value of the pixels within the fingerprint region as the mean vector, thus achieving the fingerprint image segmentation effectively. Experimental results show that the background area and fuzzy algorithm can accurately be separated from fingerprint image with the algorithm. The algorithm improves the accuracy of segmentation and has good accuracy for most of fingerprint images.
出处
《吉林大学学报（理学版）》
CAS
CSCD
北大核心
2012年第5期1011-1014,共4页
Journal of Jilin University:Science Edition
基金
吉林省教育厅"十二五"规划自然科学重点项目基金(批准号:2012370)
关键词
指纹图像
图像分割
均值向量
fingerprint image
image division
mean vector
