The Scanreference photogrammetry system includes 149 magnetic coded targets and PDFs for printing 192 more targets. However, while measuring something that isn’t ferromagnetic, the magnetic targets aren’t particularly helpful, and the 192 printable coded targets aren’t always enough. Unfortunately, AICON wouldn’t provide the full set of printable coded targets when I asked and instead tried to sell me a multi-thousand dollar software package for generating printable coded targets. Instead, I looked in the literature and found multiple references to a 1991 paper1 as the original publication about the ring code targets. Unfortunately, the paper is not available electronically, so I had to request a copy via interlibrary loan; I received a copy just to find out that it didn’t include any technical details on the targets.
Fortunately, further research turned up expired German patent DE19733466A1. The patent contains all of the details needed to generate the ring codes for the coded targets, except for the exact parameters and numbering scheme used for the Scanreference targets. This missing information was fairly straightforward to figure out—the targets are 14-bit with no restrictions on the number of transitions from black segments to white segments and are ordered by increasing binary value. With this information, I was then able to write a script to generate the ring codes and a script to generate a set of printable targets, resulting in a PDF with all 516 targets ready to print on stickers.
Schneider, C. T. “3-D Vermessung von Oberflächen und Bauteilen durch Photogrammetrie und Bildverarbeitung.” Proc. IDENT/VISION 91 (1991): 14-17. ↩
The “category10” color palette, originally developed by Tableau, was adopted as the default color cycle for Matplotlib 2.0 and is also used by default by D3.js and Vega, along with other software packages. While more aesthetically pleasing than the old Matplotlib default, it is unfortunately not colorblind-friendly.1 In an effort to improve this and promote the development of colorblind-friendly color cycles for scientific visualization, I built a color cycle picker that incorporates color vision deficiency simulation and enforces a minimum perceptual distance between colors, for both normal and anomalous trichromats. This is accomplished by performing color vision deficiency simulations2 for various types of deficiencies and enforcing a minimum perceptual difference for the simulated colors using the CAM02-UCS3 perceptually uniform color space (each type of deficiency is treated separately). Additionally, a minimum lightness distance is enforced, for better grayscale printability. The tool allows colors to be picked from a visualization of the CAM02-UCS color gamut and assembled into a color cycle. This visualization is performed using hardware-accelerated WebGL to allow for real-time interactive adjustment of parameters; the resulting palette is also visualized. The minimum perceptual color distance, lightness distance, and color vision deficiency simulation parameters are all adjustable. A hosted copy is provided, and the code is available in a repository on GitHub.
Personally, I have difficulty telling the second and third colors apart. ↩
G. M. Machado, M. M. Oliveira and L. A. F. Fernandes, “A Physiologically-based Model for Simulation of Color Vision Deficiency,” in IEEE Transactions on Visualization and Computer Graphics, vol. 15, no. 6, pp. 1291-1298, Nov.-Dec. 2009. doi:10.1109/TVCG.2009.113↩
Luo M.R., Li C. (2013) CIECAM02 and Its Recent Developments. In: Fernandez-Maloigne C. (eds) Advanced Color Image Processing and Analysis. Springer, New York, NY. doi:10.1007/978-1-4419-6190-7_2↩
Yesterday, I released Pannellum 2.4.0. It doesn’t contain any major new features, although it does finally include translation support, which was an often requested feature. Also included are numerous minor improvements, a few new API functions, and quite a few bug fixes; see the changelog for full details. It had been more than a year since the last release—and I’ve been meaning to create a new release for a few months—so it was high time for a new release.
Amazon recently released the Echo Button, a Bluetooth Low Energy device designed for use with Echo devices (which I don’t own). Although it uses Bluetooth instead of Wi-Fi, I thought it might be a better device to repurpose than the Dash Button, due to its larger size and easily replaceable battery. Thus, I bought one to take apart.
As part of a Halloween costume (I was a “bright idea”), I designed a light bulb PCB, which was mostly just an excuse to try out PCBmodE. It consists of seven addressable RGB LEDs, an ATtiny85 microcontroller, an ambient light sensor, and a rechargeable battery. The battery and an old hard drive magnet, for mounting the PCB, are attached to the back via double-sided tape. As one might expect, PCBmodeE worked well for this artistic circuit board design, given that it was designed to be used for something like this, but KiCad is much easier to use for just about everything else.