数学思想方法-python计算战(8)-机器视觉-二值化

二值化

hreshold

Applies a fixed-level threshold to each array element.

C++: double threshold(InputArray src, OutputArray dst, double thresh, doublemaxval, int type)

Python: cv2.threshold(src, thresh, maxval, type[, dst]) → retval, dst

C: double cvThreshold(const CvArr* src, CvArr* dst, double threshold, doublemax_value, int threshold_type)

Parameters:	src – input array (single-channel, 8-bit or 32-bit floating point). dst – output array of the same size and type as src. thresh – threshold value. maxval – maximum value to use with the THRESH_BINARY andTHRESH_BINARY_INV thresholding types. type – thresholding type (see the details below).

The function applies fixed-level thresholding to a single-channel array. The function is typically used to get a bi-level (binary) image out of a grayscale image (compare() could be also used for this purpose) or for removing a noise, that is, filtering out pixels with too small or too large values. There are several types of thresholding supported by the function. They are determined by type :

• THRESH_BINARY

  

• THRESH_BINARY_INV

  

• THRESH_TRUNC

  

• THRESH_TOZERO

  

• THRESH_TOZERO_INV

  

Also, the special value THRESH_OTSU may be combined with one of the above values. In this case, the function determines the optimal threshold value using the Otsu’s algorithm and uses it instead of the specified thresh . The function returns the computed threshold value. Currently, the Otsu’s method is implemented only for 8-bit images.

import cv2

fn="test3.jpg"
myimg=cv2.imread(fn)
img=cv2.cvtColor(myimg,cv2.COLOR_BGR2GRAY)



retval, newimg=cv2.threshold(img,40,255,cv2.THRESH_BINARY)
cv2.imshow(‘preview‘,newimg)
cv2.waitKey()
cv2.destroyAllWindows()

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http://blog.csdn.net/myhaspl/

自适应二值化

adaptiveThreshold函数能够二值化，也能够提取边缘：

Python: cv2.adaptiveThreshold(src, maxValue, adaptiveMethod, thresholdType, blockSize, C[, dst]) → dst