An image patch matching method based on multi-feature fusion

Xiangru Yu, Yukun Guo, Jinping Li, Fudong Cai
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引用次数: 2

Abstract

Appropriate features are very important for the robustness and effectiveness of matching algorithms. In general, current algorithms depend on descriptors like SIFT, SURF, which makes them only care about information of key points while ignoring the knowledge of the whole image, thus those methods are easy to result in false matches. We propose a novel matching method called multi-feature fusion, which takes full advantage of geometric, gray, color and texture features. Then we validate the effect of our method using images captured from practical applications. Experiments show the method can effectively complete the matching task of image patch.
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一种基于多特征融合的图像补丁匹配方法
合适的特征对匹配算法的鲁棒性和有效性至关重要。一般来说,目前的算法依赖于SIFT、SURF等描述符,这使得它们只关心关键点的信息,而忽略了对整个图像的了解,因此这些方法容易导致错误匹配。我们提出了一种新的多特征融合匹配方法,该方法充分利用了图像的几何特征、灰度特征、颜色特征和纹理特征。然后用实际应用中捕获的图像验证了我们的方法的效果。实验表明,该方法能有效地完成图像patch的匹配任务。
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