摘自于OpenCV Doc2.410，opencv2refman文档.

1.函数原型

adaptiveThreshold
//Applies an adaptive threshold to an array.
C++: void adaptiveThreshold(InputArray src, OutputArray dst, double maxValue, int adaptiveMethod,int thresholdType, int blockSize, double C)
Python: cv2.adaptiveThreshold(src, maxValue, adaptiveMethod, thresholdType, blockSize, C[, dst ]) !dst
C: void cvAdaptiveThreshold(
const CvArr* src, CvArr* dst, double max_value,
int adaptive_method=CV_ADAPTIVE_THRESH_MEAN_C, int threshold_type=CV_THRESH_BINARY,
int block_size=3, double param1=5)
Python: cv.AdaptiveThreshold(src, dst, maxValue, adaptive_method=CV_ADAPTIVE_THRESH_MEAN_C,thresholdType=CV_THRESH_BINARY, blockSize=3, param1=5) !
None
Parameters
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 .

2.图片处理效果

原始图片：

处理效果：

对比Canny的处理效果：

结果就差一个反色处理？

Canny+反色

3.方法分析

参考链接：http://blog.chinaunix.net/uid-20805029-id-1704893.html

函数 cvAdaptiveThreshold 将灰度图像变换到二值图像；

对方法 CV_ADAPTIVE_THRESH_MEAN_C，先求出块中的均值，再减掉param1。

     对方法 CV_ADAPTIVE_THRESH_GAUSSIAN_C ，先求出块中的加权和(gaussian)， 再减掉param1。

参数不同会产生不同的转换效果.