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一种基于指纹中心点的匹配算法 被引量:12
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作者 谭台哲 宁新宝 +1 位作者 尹义龙 詹小四 《南京大学学报(自然科学版)》 CAS CSCD 北大核心 2003年第4期483-490,共8页
针对基于点模式匹配的指纹匹配算法速度较慢的现状,研究了一种基于指纹中心点的指纹匹配算法。该算法首先根据指纹模式区中检测的奇异点结构特征信息对指纹进行粗匹配,判断指纹不匹配的情况。其次,对无法判断的情形,则进行精确匹配,进... 针对基于点模式匹配的指纹匹配算法速度较慢的现状,研究了一种基于指纹中心点的指纹匹配算法。该算法首先根据指纹模式区中检测的奇异点结构特征信息对指纹进行粗匹配,判断指纹不匹配的情况。其次,对无法判断的情形,则进行精确匹配,进一步利用奇异点或者指纹有效区域的质心点寻找匹配的基准特征点对和相应的变换参数,并将待识指纹相对于模板指纹做姿势纠正,最后采用坐标匹配的方式实现两枚指纹的比对。实验结果证明,该算法可以快速、准确的定位基准点,精确求取变换参数,误识率低,准确性高,并具有图像旋转平移不变性。对面积适中的指纹图像,匹配结果可以满足在线应用的需要。 展开更多
关键词 指纹图像 指纹匹配算法 图像匹配 指纹奇异 基准特征点 指纹中心
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一种新的指纹匹配方法 被引量:14
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作者 王业琳 宁新宝 尹义龙 《中国图象图形学报(A辑)》 CSCD 北大核心 2003年第2期203-208,共6页
针对基于点模式匹配的指纹匹配算法速度较慢的现状 ,设计了一种新的指纹匹配方法 ,即利用纹线匹配技术来寻找基准点对的指纹匹配算法 .该算法首先基于指纹纹线的相似程度寻找一对基准特征点 ;然后根据基准点对的坐标 ,计算两幅指纹图象 ... 针对基于点模式匹配的指纹匹配算法速度较慢的现状 ,设计了一种新的指纹匹配方法 ,即利用纹线匹配技术来寻找基准点对的指纹匹配算法 .该算法首先基于指纹纹线的相似程度寻找一对基准特征点 ;然后根据基准点对的坐标 ,计算两幅指纹图象 (模板图象、待识图象 )的相对平移和旋转参数 ,并将待识图象相对于模板图象进行图象姿势纠正 ;最后使用坐标匹配的方法统计两幅图象能够匹配的特征点数目 ,以实现两枚指纹的匹配 .实验证明 ,该算法匹配速度很快 ,误识率低 ,准确性高 ,并具有图象旋转平移不变性 .对面积适中的指纹图象 ,匹配结果可以满足在线应用的需要 .该算法有望发展成为一种实用。 展开更多
关键词 计算机图象处理 指纹匹配 纹线匹配 纹线离散采样 基准特征点
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Fast uniform content-based satellite image registration using the scale-invariant feature transform descriptor 被引量:3
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作者 Hamed BOZORGI Ali JAFARI 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2017年第8期1108-1116,共9页
Content-based satellite image registration is a difficult issue in the fields of remote sensing and image processing. The difficulty is more significant in the case of matching multisource remote sensing images which ... Content-based satellite image registration is a difficult issue in the fields of remote sensing and image processing. The difficulty is more significant in the case of matching multisource remote sensing images which suffer from illumination, rotation, and source differences. The scale-invariant feature transform (SIFT) algorithm has been used successfully in satellite image registration problems. Also, many researchers have applied a local SIFT descriptor to improve the image retrieval process. Despite its robustness, this algorithm has some difficulties with the quality and quantity of the extracted local feature points in multisource remote sensing. Furthermore, high dimensionality of the local features extracted by SIFT results in time-consuming computational processes alongside high storage requirements for saving the relevant information, which are important factors in content-based image retrieval (CBIR) applications. In this paper, a novel method is introduced to transform the local SIFT features to global features for multisource remote sensing. The quality and quantity of SIFT local features have been enhanced by applying contrast equalization on images in a pre-processing stage. Considering the local features of each image in the reference database as a separate class, linear discriminant analysis (LDA) is used to transform the local features to global features while reducing di- mensionality of the feature space. This will also significantly reduce the computational time and storage required. Applying the trained kernel on verification data and mapping them showed a successful retrieval rate of 91.67% for test feature points. 展开更多
关键词 Content-based image retrieval Feature point distribution Image registration Linear discriminant analysis REMOTESENSING Scale-invariant feature transform
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