Profanity alert!

I wrote a program to check the curse words and let you know when you are talking! (Profanity alert)

Speech works on Windows: https://pypi.python.org/pypi/speech/0.5.2

Talk:
You said We are talking about image processing
This documents has no curse words!
Talk:You said Our system
This documents has no curse words!
Talk:
You said And now we are talking about speech processing This documents has no curse words!
Talk:
You said Great This documents has no curse words!
Talk:

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Hand detection using contour method

Contours can be explained simply as a curve joining all the continuous points (along the boundary), having same color or intensity. The contours are a useful tool for shape analysis and object detection and recognition.

There are 3 flags under cv2.findContours()┬ácategory, but I am discussing only the first two – cv2.CHAIN_APPROX_NONE and cv2.CHAIN_APPROX_SIMPLE.

First one finds all the points on the contour or the boundary. But actually do we need all the points? For e.g. , you found the contour of a straight line. Do you need all the points on the line to represent that line? No, we need just two end points of that line. This is what second flag does. It removes all redundant points and compresses the contour.

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Hand detection (using skin tone)

Hand detection using skin tone is the simplest way to detect hand. Problems of this method are the background should not contain skin colored, really sensitive to light and shape of background!

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Object tracking

Tracking of the blue object (and also my glasses which are blue as well ;D)

Tracking of the blue object (and also my glasses which are blue as well ;D)

  1. Take each frame of the video
  2. Convert from BGR to HSV color-space (HSV, it is more easier to represent a color than RGB color-space)
  3. We threshold the HSV image for a range of blue color
  4. Now extract the blue object, we can do whatever on that image we want.

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