In this repository ,we are using "Temporal median filter" with opencv in cpp.
_The General steps of the thermal(or temporal median) median filter is :
- Convert the background template to grayscale
- Loop all the frames of the video.then extract the current frame,and convert it to grayscale.
- Calcule the absolute diffrence between the current frame and the background model.
- Apply threshold to remove noise and binarize the output(only 0 and 1 or only 0 and 255)
_Documents that will help about bacground substracion:
# https://docs.opencv.org/3.4/d1/d5c/classcv_1_1bgsegm_1_1BackgroundSubtractorGMG.html
# https://docs.opencv.org/3.4/d6/da7/classcv_1_1bgsegm_1_1BackgroundSubtractorMOG.html
# https://docs.opencv.org/3.4/d7/d7b/classcv_1_1BackgroundSubtractorMOG2.html
# https://docs.opencv.org/3.4/db/d88/classcv_1_1BackgroundSubtractorKNN.html
# https://docs.opencv.org/3.4/de/dca/classcv_1_1bgsegm_1_1BackgroundSubtractorCNT.html
_Documents that will help,anyone*:
# https://docs.opencv.org/master/d0/d86/tutorial_py_image_arithmetics.html
# https://www.pyimagesearch.com/2021/01/19/opencv-bitwise-and-or-xor-and-not/
-CREATOR: mortza-
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