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• W2938458040 abstract "We propose a local feature descriptor based on moment. Although conventional scale invariant feature transform (SIFT)-based algorithms generally use difference of Gaussian (DoG) for feature extraction, they remain sensitive to more complicated deformations. To solve this problem, we propose MIFT, an invariant feature transform algorithm based on the modified discrete Gaussian-Hermite moment (MDGHM). Taking advantage of MDGHM’s high performance to represent image information, MIFT uses an MDGHM-based pyramid for feature extraction, which can extract more distinctive extrema than the DoG, and MDGHM-based magnitude and orientation for feature description. We compared the proposed MIFT method performance with current best practice methods for six image deformation types, and confirmed that MIFT matching accuracy was superior of other SIFT-based methods." @default.
• W2938458040 created "2019-04-25" @default.
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• W2938458040 date "2019-04-11" @default.
• W2938458040 modified "2023-09-26" @default.
• W2938458040 title "MIFT: A Moment-Based Local Feature Extraction Algorithm" @default.
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• W2938458040 doi "https://doi.org/10.3390/app9071503" @default.
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