Python 自适应阈值参数混淆
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Adaptive Threshold parameters confusion
提问by Maryam Tahir
Can anyone please tell me what are the parameters in these Adaptive Threshold functions and how are they controlling black and white pixels.
谁能告诉我这些自适应阈值函数中的参数是什么以及它们如何控制黑白像素。
cv2.adaptiveThreshold(img,255,cv2.ADAPTIVE_THRESH_MEAN_C,\
cv2.THRESH_BINARY,11,2)
th3 = cv2.adaptiveThreshold(img,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,\
cv2.THRESH_BINARY,11,2)
采纳答案by GPPK
Python: cv2.adaptiveThreshold(src, maxValue, adaptiveMethod, thresholdType, blockSize, C[, dst]) → dst
Parameters:
参数：
src – Source 8-bit single-channel image.
dst – Destination image of the same size and the same type as src .
maxValue – Non-zero value assigned to the pixels for which the condition is satisfied. See the details below.
adaptiveMethod – Adaptive thresholding algorithm to use, ADAPTIVE_THRESH_MEAN_C or ADAPTIVE_THRESH_GAUSSIAN_C . See the details below.
thresholdType – Thresholding type that must be either THRESH_BINARY or THRESH_BINARY_INV .
blockSize – Size of a pixel neighborhood that is used to calculate a threshold value for the pixel: 3, 5, 7, and so on.
C – Constant subtracted from the mean or weighted mean (see the details below). Normally, it is positive but may be zero or negative as well.
Taken from here:and it also explains the method in a lot more detail.
取自此处：并且还更详细地解释了该方法。
回答by meelo
Add to the answer from GPPK.
添加到 GPPK 的答案中。
The function transforms a grayscale image to a binary image according to the formulae:
该函数根据以下公式将灰度图像转换为二值图像：
- THRESH_BINARY
- THRESH_BINARY
- THRESH_BINARY_INV
- THRESH_BINARY_INV
where T(x,y) is a threshold calculated individually for each pixel.
其中 T(x,y) 是为每个像素单独计算的阈值。
- For the method ADAPTIVE_THRESH_MEAN_C , the threshold value T(x,y) is a mean of the blockSize x blockSize neighborhood of (x, y) minus C .
- For the method ADAPTIVE_THRESH_GAUSSIAN_C , the threshold value T(x, y) is a weighted sum (cross-correlation with a Gaussian window) of the blockSize x blockSize neighborhood of (x, y) minus C . The default sigma (standard deviation) is used for the specified blockSize .
- 对于 ADAPTIVE_THRESH_MEAN_C 方法，阈值 T(x,y) 是 (x, y) 减去 C 的 blockSize x blockSize 邻域的平均值。
- 对于方法 ADAPTIVE_THRESH_GAUSSIAN_C ，阈值 T(x, y) 是 (x, y) 减去 C 的 blockSize x blockSize 邻域的加权和（与高斯窗口的互相关）。默认 sigma（标准偏差）用于指定的 blockSize 。
