黄源,张福泉

• 1:重庆航天职业技术学院计算机系
• 2:北京理工大学软件学院

摘要(Abstract)：

为解决当前图像匹配算法忽略了相邻图像层次间灰度量级的差异性导致的较多的误检与漏检现象,使其匹配精度不高的问题,本文设计了基于差分制约模型与三角网优化的图像匹配技术.首先,利用差分高斯函数来构造差分制约方法,对相邻图像层次间的灰度量级进行一致性约束,准确提取图像特征点;然后,通过计算圆形邻域内的Haar小波响应值,确定特征点的主方向;再计算圆形邻域内的梯度与灰度特征,得到相应的特征向量;利用主方向与特征向量来生成实现特征点描述符.利用特征点描述符求取特征点之间欧氏距离的最近邻与次近邻比值,对图像特征完成初步匹配;最后,通过初匹配之间的空间关系构建三角网约束规则,对错误匹配特征点进行剔除,对匹配结果进行优化.实验结果表明:与当前图像匹配算法相比,所提算法具有更高的匹配正确度与鲁棒性.

关键词(KeyWords)： 图像匹配;差分制约模型;Haar小波;欧氏距离;差分高斯函数;三角网约束规则

Abstract:

Keywords:

基金项目(Foundation): 重庆市教育委员会科学技术研究计划青年项目资助(KJQN201803002)

作者(Author): 黄源,张福泉

DOI: 10.13568/j.cnki.651094.2018.04.008

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