Converting an OpenCV Image to Black and White

Question

How do you convert a grayscale OpenCV image to black and white  I see a similar question has already been asked  but I m using OpenCV 2 3  and the proposed solution no longer seems to work   I m trying to convert a greyscale image to black and white  so that anything not absolutely black is white  and use this as a mask for surf detect    in order to ignore keypoints found on the edge of the black mask area   The following Python gets me almost there  but the threshold value sent to Threshold   doesn t appear to have any effect  If I set it to 0 or 16 or 128 or 255  the result is the same  with all pixels with a value   128 becoming white  and everything else becoming black   What am I doing wrong   import cv  cv2 fn    myfile jpg  im gray   cv2 imread fn  cv CV LOAD IMAGE GRAYSCALE  im gray mat   cv fromarray im gray  im bw   cv CreateImage cv GetSize im gray mat   cv IPL DEPTH 8U  1   im bw mat   cv GetMat im bw  threshold   0   128 255  HAS NO EFFECT     cv Threshold im gray mat  im bw mat  threshold  255  cv CV THRESH BINARY   cv CV THRESH OTSU   cv2 imshow     np asarray im bw mat   cv2 waitKey

User · Answer

Specifying CV THRESH OTSU causes the threshold value to be ignored  From the documentation       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    This code reads frames from the camera and performs the binary threshold at the value 20    include  opencv2 core core hpp   include  opencv2 imgproc imgproc hpp   include  opencv2 highgui highgui hpp   using namespace cv   int main int argc  const char   argv           VideoCapture cap       if argc  gt  1           cap open string argv 1          else          cap open 0        Mat frame       namedWindow  video   1        for               cap  gt  gt  frame           if  frame data               break           cvtColor frame  frame  CV BGR2GRAY           threshold frame  frame  20  255  THRESH BINARY           imshow  video   frame            if waitKey 30   gt   0               break             return 0

User · Answer

Approach 1 While converting a gray scale image to a binary image  we usually use cv2 threshold   and set a threshold value manually  Sometimes to get a decent result we opt for Otsu s binarization  I have a small hack I came across while reading some blog posts   Convert your color  RGB  image to gray scale  Obtain the median of the gray scale image  Choose a threshold value either 33  above the median   Why 33   This is because 33  works for most of the images data-set  You can also work out the same approach  by replacing median with the mean  Approach 2 Another approach would be to take an x number of standard deviations  std  from the mean  either on the positive or negative side  and set a threshold  So it could be one of the following   th1   mean -  x   std  th2   mean    x   std   Note  Before applying threshold it is advisable to enhance the contrast of the gray scale image locally  See CLAHE

User · Answer

For those doing video I cobbled the following based on  tsh    import cv2 as cv import numpy as np  def nothing x  pass  cap   cv VideoCapture 0  cv namedWindow  videoUI   cv WINDOW NORMAL  cv createTrackbar  T   videoUI  0 255 nothing   while True       ret  frame   cap read       vid gray   cv cvtColor frame  cv COLOR BGR2GRAY      thresh   cv getTrackbarPos  T   videoUI        vid bw   cv threshold vid gray  thresh  255  cv THRESH BINARY  1       cv imshow  videoUI  cv flip vid bw 1        if cv waitKey 1   amp  0xFF    ord  q            break  cap release   cv destroyAllWindows     Results in

User · Answer

Pay attention  if you use cv CV THRESH BINARY means every pixel greater than threshold becomes the maxValue  in your case 255   otherwise the value is 0  Obviously if your threshold is 0 everything becomes white  maxValue   255  and if the value is 255 everything becomes black  i e  0    If you don t want to work out a threshold  you can use the Otsu s method  But this algorithm only works with 8bit images in the implementation of OpenCV  If your image is 8bit use the algorithm like this   cv Threshold im gray mat  im bw mat  threshold  255  cv CV THRESH BINARY   cv CV THRESH OTSU    No matter the value of threshold if you have a 8bit image

User · Answer

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

User · Answer

Simply you can write the following code snippet to convert an OpenCV image into a grey scale image  import cv2 image   cv2 imread  image jpg  0  cv2 imshow  grey scale image  image    Observe that the image jpg and the code must be saved in same folder    Note that      image jpg   gives a RGB image   image jpg  0  gives Grey Scale Image

User · Answer

Here s a two line code I found online that might be helpful for a beginner    Absolute value of the 32 64 abs image in32 64   np absolute image in32 64   image 8U   np uint8 abs image in32 64

[python] Converting an OpenCV Image to Black and White

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