A Raspberry Pi Night Vision Camera (Shallow Thoughts)

A Raspberry Pi Night Vision Camera

When I built my http://shallowsky.com/blog/hardware/raspberry-pi-motion-camera.html (and part 2), I always had the NoIR camera in the back of my mind. The NoIR is a version of the Pi camera module with the infra-red blocking filter removed, so you can shoot IR photos at night without disturbing nocturnal wildlife (or alerting nocturnal burglars, if that's your target).

After I got the daylight version of the camera working, I ordered a NoIR camera module and plugged it in to my RPi. I snapped some daylight photos with raspstill and verified that it was connected and working; then I waited for nightfall.

In the dark, I set up the camera and put my cup of hot chocolate in front of it. Nothing. I hadn't realized that although CCD cameras are sensitive in the near IR, the wavelengths only slightly longer than visible light, they aren't sensitive anywhere near the IR wavelengths that hot objects emit. For that, you need a special thermal camera. For a near-IR CCD camera like the Pi NoIR, you need an IR light source.

Knowing nothing about IR light sources, I did a search and came up with something called a "Infrared IR 12 Led Illuminator Board Plate for CCTV Security CCD Camera" for about $5. It seemed similar to the light sources used on a few pages I'd found for home-made night vision cameras, so I ordered it. Then I waited, because I stupidly didn't notice until a week and a half later that it was coming from China and wouldn't arrive for three weeks. Always check the shipping time when ordering hardware!

When it finally arrived, it had a tiny 2-pin connector that I couldn't match locally. In the end I bought a package of female-female SchmartBoard jumpers at Radio Shack which were small enough to make decent contact on the light's tiny-gauge power and ground pins. I soldered up a connector that would let me use a a universal power supply, taking a guess that it wanted 12 volts (most of the cheap LED rings for CCD cameras seem to be 12V, though this one came with no documentation at all). I was ready to test.

Testing the IR light

One problem with buying a cheap IR light with no documentation: how do you tell if your power supply is working? Since the light is completely invisible.

The only way to find out was to check on the Pi. I didn't want to have to run back and forth between the dark room where the camera was set up and the desktop where I was viewing raspistill images. So I started a video stream on the RPi:

$ raspivid -o - -t 9999999 -w 800 -h 600 | cvlc -vvv stream:///dev/stdin --sout '#rtp{sdp=rtsp://:8554/}' :demux=h264

Then, on the desktop: I ran vlc, and opened the network stream:
rtsp://pi:8554/
(I have a "pi" entry in /etc/hosts, but using an IP address also works).

Now I could fiddle with hardware in the dark room while looking through the doorway at the video output on my monitor.

It took some fiddling to get a good connection on that tiny connector ... but eventually I got a black-and-white view of my darkened room, just as I'd expect under IR illumination. I poked some holes in the milk carton and used twist-ties to seccure the light source next to the NoIR camera.

Lights, camera, action

Next problem: mute all the blinkenlights, so my camera wouldn't look like a christmas tree and scare off the nocturnal critters.

The Pi itself has a relatively dim red run light, and it's inside the milk carton so I wasn't too worried about it. But the Pi camera has quite a bright red light that goes on whenever the camera is being used. Even through the thick milk carton bottom, it was glaring and obvious. Fortunately, you can disable the Pi camera light: edit /boot/config.txt and add this line

disable_camera_led=1

My USB wi-fi dongle has a blue light that flickers as it gets traffic. Not super bright, but attention-grabbing. I addressed that issue with a triple thickness of duct tape.

The IR LEDs -- remember those invisible, impossible-to-test LEDs? Well, it turns out that in darkness, they emit a faint but still easily visible glow. Obviously there's nothing I can do about that -- I can't cover the camera's only light source! But it's quite dim, so with any luck it's not spooking away too many animals.

Results, and problems

For most of my daytime testing I'd used a threshold of 30 -- meaning a pixel was considered to have changed if its value differed by more than 30 from the previous photo. That didn't work at all in IR: changes are much more subtle since we're seeing essentially a black-and-white image, and I had to divide by three and use a sensitivity of 10 or 11 if I wanted the camera to trigger at all.

With that change, I did capture some nocturnal visitors, and some early morning ones too. Note the funny colors on the daylight shots: that's why cameras generally have IR-blocking filters if they're not specifically intended for night shots.

Here are more photos, and larger versions of those: Images from my night-vision camera tests.

But I'm not happy with the setup. For one thing, it has far too many false positives. Maybe one out of ten or fifteen images actually has an animal in it; the rest just triggered because the wind made the leaves blow, or because a shadow moved or the color of the light changed. A simple count of differing pixels is clearly not enough for this task.

Of course, the software could be smarter about things: it could try to identify large blobs that had changed, rather than small changes (blowing leaves) all over the image. I already know SimpleCV runs fine on the Raspberry Pi, and I could try using it to do object detection.

But there's another problem with detection purely through camera images: the Pi is incredibly slow to capture an image. It takes around 20 seconds per cycle; some of that is waiting for the network but I think most of it is the Pi talking to the camera. With quick-moving animals, the animal may well be gone by the time the system has noticed a change. I've caught several images of animal tails disappearing out of the frame, including a quail who visited yesterday morning. Adding smarts like SimpleCV will only make that problem worse.

So I'm going to try another solution: hooking up an infra-red motion detector. I'm already working on setting up tests for that, and should have a report soon. Meanwhile, pure image-based motion detection has been an interesting experiment.