Schlagwort: light-painting

  • Use light painting to visualize magnetic fields

    Use light painting to visualize magnetic fields

    Reading Time: 2 minutes

    Light painting is a photography trick that exploits a camera’s shutter. To ensure proper exposure in different lighting conditions, cameras have variable shutter speeds. If the subject is well-lit, then the shutter may only remain open for ten or so milliseconds. But if the subject is very dark, then a photographer may choose to leave the shutter open for minutes. Anything bright that moves in the frame will leave “painted” streaks. This project takes advantage of light painting to visualize magnetic fields.

    Because exposure (both for film cameras and digital cameras) relies on brightness, anything dark that moves in a long exposure photo will be barely visible. But anything bright (LEDs, in this case) will be very visible. For this project, Chris Hill wears an LED array on their fingertip. When they capture a long exposure photo, their hand is dark and almost invisible. But the LEDs, which illuminate in response to the presence of magnetic fields, are bright and show up clearly in the picture. The result is a light painting of magnetic fields that would otherwise be invisible to the human eye.

    The LEDs (an Adafruit NeoPixel Stick) and ultrahigh sensitivity analog sensor (to detect the strength of magnetic fields) are worn on the finger, but the rest of the electronic components reside in a 3D-printed enclosure that straps to the forearm. That enclosure contains an Arduino Nano 33 BLE board, an Adafruit MiniBoost 5V power module, and a 2500mAh LiPo battery. The Arduino monitors the strength of the magnetic fields detected by the sensor and then activates a proportional number of LEDs on the NeoPixel Stick. In the light-painted photo, this presents as a series of overlaid bar graphs that depict the magnetic field strength in their positions.

    The post Use light painting to visualize magnetic fields appeared first on Arduino Blog.

    Website: LINK

  • Light painting with a CNC router

    Light painting with a CNC router

    Reading Time: < 1 minute

    Light painting with a CNC router

    Arduino TeamMarch 6th, 2019

    Maker Jeremy S. Cook has experimented with both CNC machinery and light painting in the past, and decided to combine these two skills into a new artistic device. 

    His setup uses a web app found here to program a CNC router as a sort of dot matrix printer. But instead of a pen, pencil, brush or other marking utensil, it uses a button as an input to the onboard Arduino Nano when pressed to the router’s surface.

    From this input, the Arduino then commands a diffused RGB LED to “mark” the surface with light, painting an image on the camera’s exposed sensor. 

    Code and print files are are available on GitHub if you’d like to try your own light art experiments!

    [youtube https://www.youtube.com/watch?v=Y_4NdVgSwuA?feature=oembed&w=500&h=281]

    Website: LINK

  • Light painting rig is a masterpiece of artistic hardware hacking

    Light painting rig is a masterpiece of artistic hardware hacking

    Reading Time: 2 minutes

    Light painting rig is a masterpiece of artistic hardware hacking

    Arduino TeamJuly 30th, 2018

    Light painting is an art form where dark areas are selectively lit to form interesting effects. While normally a manual operation, Josh Sheldon has come up with a rig to automate and enhance the process. The results are nothing short of spectacular, producing not static images, but astonishing animated light displays.

    His device resembles a 3D printer made out of aluminum extrusion. X,Y, and Z axes are controlled by a series of stepper motors, but it uses a point of controlled light instead of melted plastic to form shapes. 

    Light animations are set up in Blender, and a hardware and software toolchain including Processing, an Arduino Mega, and a Dragonframe module are implemented for control.

    Check out the whole story in the video below, or see code/build documentation are available on GitHub.

    [youtube https://www.youtube.com/watch?v=O1bY66X1JKA?feature=oembed&w=500&h=281]

    Website: LINK