sarahhowell – PhotoGeometry

Optimization for Diffraction Grating Groove Data

sarahhowellAugust 1, 2019Leave a comment

Utilizing the scripts outlined in previous blog posts by Grady and I, we were able to create an optimization function to solve for the groove distance and orientation of the diffraction gratings on our holographic glitter sheet.

Using the data gathered from the plot, pictured above, we were able to get the angles needed for our diffraction grating formula

With the left half of the equation solved using the angles we got from our graph, and the wavelength solved using the method outlined in last week’s blog post about wavelengths, we were able to create an optimization function to solve for our missing information: the distance between the grooves and the orientation of the grooves.

However, there seems to be multiple combinations of orientations and groove distances that can produce the same angle combinations, therefore we need to use more information for our optimization function.

We decided to use all of the lines from a lit square on the monitor to one glitter board to see if acquiring more data to run our optimization on would provide more specific results.

However, there are still multiple combinations of distance and orientation for the grooves that result in near-zero values for the error value. To combat this, we are looking for more parameters for our optimization function that would add constraints to the answers we receive, such as a minimum or maximum value for the groove distance. We have begun working on a script that will look at all pixels and their angles to light squares on the monitor, rather than just one pixels’. Hopefully this large amount of data will produce more specific results from our optimization function.

Colors of One Holographic Glitter Pixel

sarahhowellJuly 25, 2019Leave a comment

Grady and I have been working on a script that takes in a large set of pictures of a sheet of holographic glitter, where a picture is taken at every location of a small white box moving along a monitor across from the glitter sheet. The graph we created shows the color of a single glitter pixel when the white box is at that location on the monitor. From this data, I combined the graph with the script I wrote a few weeks ago and created a graph that shows the same thing, just displaying the closest monochromatic wavelength to the RGB value shown and recording that value.

Any photo where the pixel we selected was not lit was not used for this process, as well as any photo where the pixel was fully saturated, or not saturated to at least 15%.

We plan to use these lines to compute a various set of angles that we need, along with the wavelength, to determine the groove spacing of the diffraction grating on our specific holographic glitter sheet.

Approximating Wavelengths from RGB Values

sarahhowellJuly 3, 2019Leave a comment

In the past few days I've been working on finding away to approximate the wavelengths of lights in photos. This isn't technically possible to do with complete accuracy, but I was able to write a script that can approximate the wavelength with some exceptions (mentioned later in the post).

Using data from a chart that has the XYZ colorspace of all monochromatic wavelengths of visible light, I was able to convert my RGB image to XYZ colorspace and find the closest wavelength value to the XYZ values of the pixel. I've produced a histogram of this script in action on an entire image, however I also produced a smaller version of the script that can be used as a function and convert one pixel at a time from an RGB value to wavelength value.

Here is the histogram of wavelengths of light found in the photo:
Here is a histogram of the hues present in the same photo:

As you can see, there are a few issues with the wavelength approximations. Some color hues (most notably pinks and purples) cannot be produced using a single wavelength. My script matches the RGB value of the pixel to the closest monochromatic wavelength, and therefore colors that cannot be created with one wavelength are approximated to the closest component wave, which can explain why there are larger amounts of blue and red light shown in the wavelength histogram.

This behavior seems fairly consistent across images, but in the future I might have to figure out a way to approximate these more complex colors if we find that more accuracy is needed. For now this script gives us an accurate enough idea of the wavelengths of light produced in the image in order to begin using holographic light diffraction grating equations to approximate other information such as the angle of the incoming wavelength before the diffraction occurred.