用法:
skimage.feature.corner_fast(image, n=12, threshold=0.15)
提取給定圖像的 FAST 角點。
- image:(M, N) ndarray
輸入圖像。
- n:int 可選
圓圈上 16 個像素中的最小連續像素數,這些像素都應該比 testpixel 更亮或更暗。如果 Ic < Ip - 閾值,則圓上的點 c 相對於測試像素 p 更暗,如果 Ic > Ip + 閾值則更亮。也代表FAST-n角檢測器中的n。
- threshold:浮點數,可選
用於決定圓上的像素是否更亮、更暗或類似 w.r.t 的閾值。測試像素。當需要更多拐角時降低閾值,反之亦然。
- response:ndarray
快速角響應圖像。
參數:
返回:
參考:
- 1
Rosten, E., & Drummond, T. (2006, May). Machine learning for high-speed corner detection. In European conference on computer vision (pp. 430-443). Springer, Berlin, Heidelberg. DOI:10.1007/11744023_34 http://www.edwardrosten.com/work/rosten_2006_machine.pdf
- 2
Wikipedia, “Features from accelerated segment test”, https://en.wikipedia.org/wiki/Features_from_accelerated_segment_test
例子:
>>> from skimage.feature import corner_fast, corner_peaks >>> square = np.zeros((12, 12)) >>> square[3:9, 3:9] = 1 >>> square.astype(int) array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0], [0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]) >>> corner_peaks(corner_fast(square, 9), min_distance=1) array([[3, 3], [3, 8], [8, 3], [8, 8]])
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注:本文由純淨天空篩選整理自scikit-image.org大神的英文原創作品 skimage.feature.corner_fast。非經特殊聲明,原始代碼版權歸原作者所有,本譯文未經允許或授權,請勿轉載或複製。