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I searched for what is noir camera, but i am not clear with it . Explanation about noir is appreciable.

For my project , i want the camera to monitor in both day and night time so that i should get clear images if there is some intrusions . Which camera module should i use (noir or the normal one )?

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    "For my project , i want the camera to monitor in both day and night time so that i should get clear images if there is some intrusions." -> Be warned it doesn't take pictures in the dark. It is also not "heat sensing" or anything like that. It is sensitive to the upper part of the IR spectrum. So, you can use it stealthily in the dark because you can use a light source that is not perceivable to a human being, but you still need an IR light source. Pictures taken in normal light look a bit odd, color balance wise, but they are otherwise fine.
    – goldilocks
    Sep 23, 2016 at 19:16

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Have a look at this and this for a short intro what a NoIR camera is. NoIR stands for No Infra Red filter meaning the sensor will pickup IR waves in addition to visible light which will affect the final image.

No IR comparison

  • image referenced from here, (disclaimer: photo copyright belongs to the owner)

If you need to monitor both during day and night, you'd probably have to go with 2 cameras - one that works with the IR filter for day and one without IR filter for night. as seen in the above image NoIR might not give usable results during day depending how much ambient IR is around. Since the images from the filtered (day camera) and unfiltered (night camera) will look different, I'd think you will need different algorithms for each camera to detect and identify objects in the images.

Here is pretty good documentation on the camera module and how to use it from python

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  • There's also some interesting stuff on PiNoir wavelength detection in picamera ticket #137 that's probably worth reading (basically why you can't expect to get a "normal" picture back from a PiNoir without some form of external filter).
    – Dave Jones
    Sep 23, 2016 at 20:33

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