作者
Seyed Mostafa Mousavi Kahaki, Md Jan Nordin, Amir H Ashtari, Sophia J Zahra
发表日期
2016/1/29
期刊
Neurocomputing
卷号
175
页码范围
1009-1018
出版商
Elsevier
简介
In this paper, a new deformation invariant image matching method, known as spatial orientation feature matching (SOFM), is presented. A new similarity value, which measures the similarity of the signal through the path based on triple-wise signal eigenvector correlation, is proposed. The proposed method extracts similarity feature values by relying on the distinct path between two specific interest points and following the alternation of the signal while traversing the path. Because these similarity values of the path are deformation invariant, the proposed method supports various types of transformation in the original image, such as scale, translation, rotation, intensity noises and occlusion. Moreover, the triple-wise similarity scores are accumulated in a 2-D similarity space; thus, robust matched correspondence points are obtained using cumulative similarity space. SOFM was compared to the most recent related …
引用总数
2016201720182019202020212022259642
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