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So let's start doing some bitwise operations and include in the device operations and masking because

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that's essentially what you will be using these bitwise operations for.

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They're quite handy when you have to mask images which you all seem to want to discuss but for now we'll

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just introduce the topic selflessly.

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Let's create some chips here.

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So we're going to create a square and an ellipse here.

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Now you may be familiar with creating a rectangle or square I call it because it's same dimensions.

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I decide for this one above that an ellipse is slightly different.

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It doesn't actually follow the same standard as a circle.

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You can check the open see the documentation to get some details I won't go into it in this chapter.

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Here to take up too much time.

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This run this function and we see it's here.

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So this ellipse a single left creates and has actually not a full ellipse of the parameters to create

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sort of a semi hemisphere type image here.

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So what we're going to do now we're going to overlay these images and using some bitwise operations

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to illustrate the different type of operations that we have.

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So let's get to it.

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So that's actually run some bitwise operations on the images we just created.

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So by doing that we use these open C-v functions bitwise and bitwise OR bitwise Exel and bitwise NOT.

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If you're familiar with logic gates or just on gerneral programming you'd understand that what these

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things mean.

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However it's always good to illustrate that you know images itself.

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Keep in mind that Squire and Lipps has to be of the same dimensions here which is why we created the

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canvas initially a tree rendered between two pixels.

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So that's around us.

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So before we run this I just get a refresher of what all images look like.

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So let's run it and come on what are you doing it's going to happen.

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Exactly.

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Why would you assume this would have happened.

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This is the intersection of only those two images here and by intersection I mean is that it only white

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areas.

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And keep in mind these statements here they would when you have a binary type image either black or

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white always a grayscale image.

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It's not exactly going to look like you imagine.

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You can try it on your own.

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I love it.

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I'm eliciting the concepts of these bitwise operations.

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You see this white area here and see only parts of those two images that intersected so let's look at

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it or that wise operation.

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Exactly as we anticipated both images shown here.

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Since this sort of takes the signal and the software and we do come together here.

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So what do you think exo of to do.

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Let's see.

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EXO is sort of a weird one.

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Sort of looks like a reverse.

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So the intersection between these.

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So what this means is that anything that's an axle goes back to 0 0 0 black and red remains with the

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images exist like a wall statement.

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It shows up here.

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So it can be useful some some things you can get maybe a little and figure out what you may need it

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for.

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And others are not.

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Now keep in mind not is different.

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Not just ticks into one takes from one image into consideration.

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So it's not is actually equivalent to inverse of an image and you'll see that shortly.

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So let's look at what that is.

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So let's bring it in here.

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Memorize this one.

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So this is a square run in a bitwise NOT operation as you can see it basically includes ticklers which

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is actually quite useful in many open any functions which you will come in to come across later on.

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So that's an introduction to bitwise operations.

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Hope you found it useful.