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题名: 基于改进Hausdorff距离的分层景象匹配算法
其他题名: Hierarchy scene matching algorithm based on improved Hausdorff distance
作者: 郭桂旭 ; 惠斌 ; 冯剑
作者部门: 光电信息技术研究室
关键词: Hausdorff距离 ; 景象匹配 ; 分层 ; 模糊性 ; 统计性
刊名: 计算机应用研究
ISSN号: 1001-3695
出版日期: 2014
卷号: 31, 期号:12, 页码:3837-3840
收录类别: CSCD
产权排序: 1
摘要: 模板作为一种常见的目标描述,在图像跟踪、目标识别、图像融合等方面有着广泛的应用。为克服传统的相似性度量容易受到噪声、遮挡和成像机理等因数影响的缺点,结合人的认知过程,提出了一种分层的模板匹配算法。首先利用了统计指标来对候选匹配区域进行预标记,其次通过对Hausdorff相似性度量的改进来提高其对遮挡、异源图像匹配的鲁棒性。实验结果证明了该方法能够有效地减少搜索区域大小,提高了遮挡情况下的匹配精度,验证了算法的有效性。
英文摘要: Templates, as frequently-used objects descriptions, have been widely used in many fields, such as image matching, object recognition, image fusion etc. To deal with the defect that traditional matching methods are susceptible to noise, occlusion and change of imaging mechanism, a hierarchical template matching algorithm is presented, according to human cognitive process. Firstly cut candidate matching areas by using the statistical index; then improve the robustness though an improvement algorithm based on MHD . The experimental results have impressively indicated the effectiveness of the proposed method to keep candidate matching areas down and improve the robustness.
语种: 中文
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内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/15231
Appears in Collections:光电信息技术研究室_期刊论文

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