For this tutorial I am assuming you have both math and coding knowledge!
Also for this tutorial you will need Mat Lab computer vision toolbox, an Arduino, a laser line and a webcam.
Due to popular demand I bring you the official publication: https://www.researchgate.net/publication/321668948...
HUGE thanks to my great friend Bryer C. Sousa for making this possible. I hope this helps everyone who is interested in computer vision projects!
Step 1: Building the Turn Table
The first difficulty I had making this 3D laser scanner was finding a rotating platform I could control with MatLab. Instead of spending lots of money or time I went to eBay and bought 5v Stepper Motor 28byj-48 With Drive Test Module Board Uln2003 @ http://www.ebay.com/itm/like/371474310734?lpid=82&chn=ps&ul_noapp=true For almost no money at all. I included the 3D models of the turn table I created using the stepper motor and marbles i bought at the dollar store. Just hot glue the platform to the shaft of the stepper motor and place the stepper motor in the slot within the holder. The platform should be level with marbles but be aware the cheaper the marbles the more inconsistent the diameters which may make things not level.
Step 2: Onerot() Function
The function onerot(Arduino, PauseTime, #of loops) does a basic full step sequence. If you are using the platform and stepper motor within this tutorial use a pause time of 0.005 for smooth rotation.
Code for the stepper motor found at : http://pastebin.com/7KVBUrvK
Step 3: Finishing the Setup
Once you have a method of getting an accurate rotation that can be controlled within Mat Lab set up a camera at any distance and height away from the turn table and a laser line to either the left or right of the camera at a similar distance away from the turn table. The angle of the laser should be placed optimally to cover as much of the turntable as possible but nothing has to be exact we will handle model scale difference within the code.
Step 4: Calibrate the Camera
The most important part to make this work accurately is to calibrate the camera properly. Using the MatLab computer vision toolbox I was able to obtain a accurate focal length and optical center of my camera within 0.14px accuracy. Keep in mind changing the the resolution of the camera will change the values of the calibration process.
The main values we are looking for are focal length measured in pixel units and the pixel coordinates of the optical center of the image plane.
Step 5: First Equation
Lets see how if this is true
Step 6: Converting to Camera Coordinates
In MatLab an image is represented as a matrix starting from 1,1 to max resolution. However we need to represent points in terms of camera coordinates with the optical center points at [0,0]
Step 7: Using the Basic Pinhole Equation
As we can see it works well and can be very useful if we do not know the initial value of the laser angle.
Step 8: How the Scanner Model Is Represented
As we can see lots of triangles to analyize
Step 9: Using the Law of Sin
Step 10: Equations
Ao=90 - atan(xo' / F) = 90 - atan( -225/919) = 90 - (-13.75) = 103.757
not 90-(-15.508) .
Thank you for catching that Xiaomaxiao!
Step 11: Main Algorithm
Step 14: NewFilter Function
Probably the hardest part of this scanner and the one thing i hope continues to work but this filter will do the trick to get a nice single laser line in most conditions regardless of light. The less ambient light the better.
Step 15: Variables to Change
Modify these variables in the top of the calibration script to get the script to work accurately for you
Calibration code : http://pastebin.com/CCD6bdt7
Step 16: OutPut of the Last Script
The last script generates the 2D points cloud of the scene in the steps in the image.
Step 17: Adjust the Y Axis Values
Step 18: Adjust the Y Axis Values
Step 19: Transforming the Points
Step 20: Determine Your Turntable Platform Center
Step 21: Determine How Many Loops for 360 Degrees
Step 22: Main Laser Scanner Code
Modify the top line of the code to fit your model and adjustments.
Step 23: Scan Your First Object
At this point you should be scanning models