Learning OpenCV, 2nd Edition

Table 5-2: thresholdType options for cv::threshold()

Threshold type

Operation

cv::THRESH_BINARY

DST

!

= SR C

!

> THRESH! !? !MAXVALUE ∶ 0

cv::THRESH_BINARY_INV

DST

!

= SR C

!

> THRESH! !? !0 ∶ MAXVALUE

cv::THRESH_TRUNC

DST

!

= SR C

!

> THRESH! !? !THRESH ∶ SRC

!

cv::THRESH_TOZERO

DST

!

= SR C

!

> THRESH! !? !SRC

!

∶ 0

cv::THRESH_TOZERO_INV

DST

!

= SR C

!

> THRESH! !? !0 ∶ SRC

!

Figure 5-4 should help to clarify the exact implications of each of the available values for

thresholdType, the thresholding operation.

Figure 5-4: Results of varying the threshold type in cv::threshold(); the horizontal line through each

chart represents a particular threshold level applied to the top chart and its effect for each of the five types

of threshold operations below

Let’s look at a simple example. In Example 5-1, we sum all three channels of an image and then clip the

result at 100.

Example 5-1: Example code making use of cv::threshold()

#include <opencv2/opencv.hpp>

#include <iostream>

using namespace std;

void sum_rgb( const cv::Mat& src, cv::Mat& dst ) {

// Split image onto the color planes.

vector< cv::Mat> planes;

cv::split(src, planes);

cv::Mat b = planes[0], g = planes[1], r = planes[2], s;

// Add equally weighted rgb values.

cv::addWeighted( r, 1./3., g, 1./3., 0.0, s ...