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- W2893309962 abstract "In this paper, we propose local decimal pattern (LDP) for pollen image recognition. Considering that the gradient image of pollen grains has more prominent textural features, we quantify by comparing the gradient magnitude of pixel blocks rather than the single pixel value. Unlike the local binary pattern (LBP) and its variants, we encoding by counting the pixel blocks on different quantization intervals, which makes our descriptor robust to the rotation of pollen images. In order to capture the subtle textural feature of pollen images, we increase the number of quantization intervals. The average correct recognition rate of LDP on Pollenmonitor dataset is 90.95%, which is much higher than that of other compared pollen recognition methods. The experimental results show that our method is more suitable for the practical classification and identification of pollen images than compared methods." @default.
- W2893309962 created "2018-10-05" @default.
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- W2893309962 date "2018-01-01" @default.
- W2893309962 modified "2023-09-27" @default.
- W2893309962 title "Local Decimal Pattern for Pollen Image Recognition" @default.
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- W2893309962 doi "https://doi.org/10.1007/978-3-030-01421-6_5" @default.
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