C++ – Access Mat binary images elements in OpenCV

ccomputer visionimage processingopencv

I tried the following code to print all the white pixels of this binary image without success:

Mat grayImage;
Mat rgb_Image;
int Max_value = 255;
int Global_Threshold = 155;

rgb_Image = imread( "../Tests/Object/Object.jpg", CV_LOAD_IMAGE_COLOR);   // Read the file

if(! rgb_Image.data )  // Check for invalid input
{
        cout <<  "Could not open or find the image" << endl ;
        return -1;
}

//Convert to Grayscale.
cvtColor(rgb_Image, grayImage, CV_BGR2GRAY);

//Binarize the image with a fixed threshold.
threshold( grayImage, binImage, Global_Threshold, Max_Value, 0);

//Printing white pixels
for(int i = 0; i < 640; i++)
{
    for(int j = 0; j < 480; j++)
    {
        if(255 == binImage.at<float>(i,j))
        {
            cout << binImage.at<float>(i,j) << endl;
        }
    }
}

If I print the values that are not zeroes I get strange values but not 255.

Thanks,

Best Answer

cvtColor will create a uchar image, and threshold will keep the data format, so your binImage is made up of uchars, and not float's.

Change

binImage.at<float>(i,j)

binImage.at<uchar>(i,j)

and keep in mind that comparing floats with == is usually a bad idea (even when you work with floats), because of floating-point representation errors. You may end up having a matrix full of 254.9999999999, and never meet the image(i,j)==255 condition

Related Solutions

Python – Converting an OpenCV Image to Black and White

Step-by-step answer similar to the one you refer to, using the new cv2 Python bindings:

1. Read a grayscale image

import cv2
im_gray = cv2.imread('grayscale_image.png', cv2.IMREAD_GRAYSCALE)

2. Convert grayscale image to binary

(thresh, im_bw) = cv2.threshold(im_gray, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)

which determines the threshold automatically from the image using Otsu's method, or if you already know the threshold you can use:

thresh = 127
im_bw = cv2.threshold(im_gray, thresh, 255, cv2.THRESH_BINARY)[1]

3. Save to disk

cv2.imwrite('bw_image.png', im_bw)

Opencv – Change type of Mat object from CV_32F to CV_8U

In OpenCV, if the image is of floating point type, then only those pixels can be visualized using imshow, which have value from 0.0 to 1.0, if the value is greater than 1.0, it will be shown as a white pixel and if less than 0.0, it will be shown as black pixel. To visualize a floating point image, scale its values to the range 0.0 - 1.0.

As for the conversion part.... When used with default arguments, the cv::Mat::convertTo function just creates a matrix of the specified type, and then copies the values from the source matrix and then rounds them to the nearest possible value of the destination data type. If the value is out of range, it is clamped to the minimum or maximum values.

In the documentation of imshow, it is written that:

If the image is 32-bit floating-point, the pixel values are multiplied by 255. That is, the value range [0,1] is mapped to [0,255].

It means that only the values in the range 0.0 to 1.0 will be mapped to 0 to 255. If a value is greater than 1.0, and multiplied by 255, it will become greater than 255. Then it will be clamped to the range of CV_8U and eventually it will also become 255.

In your example, all the values which are 1000, will become 255 in the destination matrix as the destination type is CV_8U and the maximum possible value is 255. All the floating point values will be floored. No automatic mapping is done.

To appropriately map the values to the range of CV_8U use the 3rd and 4th parameters of the function cv::Mat::convertTo, so that the values are scaled before the conversion is done.

Suppose the matrix A has minimum and maximum values Min and Max, where Min!=Max.

To properly scale the values from 0 to 255, you can do the following:

if (Min!=Max){ 
    A -= Min;
    A.convertTo(B,CV_8U,255.0/(Max-Min));
}

You can also do this directly like this:

if (Min!=Max)
    A.convertTo(B,CV_8U,255.0/(Max-Min),-255.0*Min/(Max-Min));

(edited taking into account zhangxaochen's comment)

Best Answer

Related Solutions

Python – Converting an OpenCV Image to Black and White

Opencv – Change type of Mat object from CV_32F to CV_8U

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