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Journal of Wood Science

Official Journal of the Japan Wood Research Society

Fig. 2 | Journal of Wood Science

Fig. 2

From: Detection and visualization of encoded local features as anatomical predictors in cross-sectional images of Lauraceae

Fig. 2

Cross-sectional image of Cinnamomum camphora (a) and keypoints in the image detected by SIFT (b), SURF (c), ORB (15,000) (d), and AKAZE (e). SIFT, SURF, ORB, and AKAZE detected 27,950, 15,159, 14,998, and 12,644 keypoints per image, respectively. The images are cropped regions of the original images. Circles in the figures indicate the location of keypoints detected by each algorithm (b–e), and their colors are randomly generated. Scale bars 100 μm

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