Learning OpenCV, 2nd Edition

When you simply pass the default values (alpha = 1.0 or beta = 0.0), you need not have

performance fears; OpenCV is smart enough to recognize these cases and not waste processor time on

useless operations.

A similar result can be achieved, with somewhat greater generality using matrix algebra:

Mat_<uchar> B = saturate_cast<uchar>(

cv::abs( src * alpha + beta )

)

This method will also generalize to types other than uchar:

Mat_<unsigned short> B = saturate_cast<unsigned short>(

cv::abs( src * alpha + beta )

)

cv::countNonZero()

int cv::countNonZero( // Return number of non-zero elements in mtx

cv::InputArray mtx, // Input array

);

count =

mtx

i

≠0

∑

1

cv::countNonZero() returns the number of nonzero pixels in the array mtx.

cv::cvarrToMat()

cv::Mat cv::cvarrToMat(

const CvArr* src, // Input array: CvMat, IplImage, or CvMatND

bool copyData = false, // if false just make new header, else copy data

bool allowND = true, // if true, and possible, convert CvMatND to Mat

int coiMode = 0 // if 0: error if COI set, if 1: ignore COI

);

cv::cvarrToMat() is used when you have an “old-style” (pre-version 2.1) image or matrix type and

you want to convert it to a “new-style” (version 2.1 or later, which uses C++) cv::Mat object. By default,

only the header for the new array is constructed without copying the data. Instead, the data pointers in the

new header ...