Normalizing histograms? [closed]

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What is normalizing histograms? When and why would I use it? What are its advantages?

I don't understand the concept at all- when I try to apply it to my histogram, when I use back projection, I don't get any results.

Could someone give me a non-technical explanation of normal开发者_如何学Pythonization?

I am using OpenCV

PS: Don't send me to wikipedia- I don't understand the Wikipedia Page

Thanks

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It's very simple, actually. A normalized histogram is one in which the sum of the frequencies is exactly 1. Therefore, if you express each frequency as a percentage of the total, you get a normalized histogram.

What is the use of a normalized histogram? Well, if you studied probability and/or statistics, you might know that one property required for a function to be a probability distribution for a random variable is that the total area under the curve is 1. That's for continuous-variable functions. For discrete functions, the requirements is that the sum of all values of the function is 1. So a normalized histogram can be thought of a probability distribution function which shows how probable each of the values of your random variable is.