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thinning.py
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thinning.py
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from scipy import weave
import numpy as np
import cv2
import sys
def _thinningIteration(im, iter):
I, M = im, np.zeros(im.shape, np.uint8)
expr = """
for (int i = 1; i < NI[0]-1; i++) {
for (int j = 1; j < NI[1]-1; j++) {
int p2 = I2(i-1, j);
int p3 = I2(i-1, j+1);
int p4 = I2(i, j+1);
int p5 = I2(i+1, j+1);
int p6 = I2(i+1, j);
int p7 = I2(i+1, j-1);
int p8 = I2(i, j-1);
int p9 = I2(i-1, j-1);
int A = (p2 == 0 && p3 == 1) + (p3 == 0 && p4 == 1) +
(p4 == 0 && p5 == 1) + (p5 == 0 && p6 == 1) +
(p6 == 0 && p7 == 1) + (p7 == 0 && p8 == 1) +
(p8 == 0 && p9 == 1) + (p9 == 0 && p2 == 1);
int B = p2 + p3 + p4 + p5 + p6 + p7 + p8 + p9;
int m1 = iter == 0 ? (p2 * p4 * p6) : (p2 * p4 * p8);
int m2 = iter == 0 ? (p4 * p6 * p8) : (p2 * p6 * p8);
if (A == 1 && B >= 2 && B <= 6 && m1 == 0 && m2 == 0) {
M2(i,j) = 1;
}
}
}
"""
weave.inline(expr, ["I", "iter", "M"])
return (I & ~M)
def thinning(src):
dst = src.copy() / 255
prev = np.zeros(src.shape[:2], np.uint8)
diff = None
while True:
dst = _thinningIteration(dst, 0)
dst = _thinningIteration(dst, 1)
diff = np.absolute(dst - prev)
prev = dst.copy()
if np.sum(diff) == 0:
break
return dst * 255
if __name__ == "__main__":
src = cv2.imread("kanji.png")
if src == None:
sys.exit()
bw = cv2.cvtColor(src, cv2.cv.CV_BGR2GRAY)
_, bw2 = cv2.threshold(bw, 10, 255, cv2.THRESH_BINARY)
bw2 = thinning(bw2)
cv2.imshow("src", bw)
cv2.imshow("thinning", bw2)
cv2.waitKey()