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Triangular Regions Representations for Matching Images With Viewpoint Changes
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DOI：10.1109/ACCESS.2022.3153525.png)
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摘要
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This paper proposes triangular region representations based on keypoints detected in images with viewpoint changes. The strongest keypoints in the reference and query images are allocated individually using a previously published contourlet-based approach to determine the keypoints. These selected keypoints serve as vertices of the triangular regions to be transformed into rectangular representations as simple numeric matrices. The suggested representation methods used to form rectangular matrices are full triangle representation (FTR) and a lighter representation called triangle medians and sides representation (TMSR). For the former, the intensity values along the lines connecting the anchor keypoint to the points between the other two triangular vertices form the rows of the representation matrix. These two triangle vertices are located in an allotted window around the anchor keypoint from the nearby keypoints. For the latter, the intensity values on the six triangular lines, medians, and sides formed the resulting rectangular matrix. The proposed representations are validated for image-matching applications using a descriptor-less matching method. Moreover, the performances of these algorithms are compared with those of traditional algorithms. The results confirmed the superiority of the proposed method over these algorithms.
Keyword:
Feature extraction
Transforms
Image matching
Image edge detection
Detectors
Shape
Licenses
Affine transformation
image matching
keypoints
triangular region representation
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
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