This week’s main goal was to continue integrating the different aspects of our project together. Shivani and Snigdha were able to integrate the image scanning and processing with the decoding algorithm and Caroline was able get the keyboard and printer integrated to the Raspberry Pis. We also started brainstorming about different ways we can make our pattern more complex and aesthetically pleasing.

Caroline

This week I integrated more of our end-to-end sender system on the first Raspberry Pi. Now, typing a message into a keyboard and hitting the button prints out the message automatically. There are two big things I am planning to get done this coming week: (1) hooking up the Raspberry Pi camera to a button on the second Pi, and (2) working to integrate the automatic printing with Snigdha’s encoding code. The biggest challenge here is that the encoding is happening in p5.js, which is browser-based, and does not have an easy way to interact with the command line for automatic printing. My starting point here will be using web sockets to communicate the keyboard input to the encoding algorithm, and then somehow sending the image to the printer, either by saving the image and running command line code, or by hosting the image on a local server and having some other command line code reach out and print it.

Snigdha

This week, I worked with Shivani and Caroline to figure out how to further beautify our encryption. More specifically, we looked at ways that the encryption could be modified to look more visually pleasing and complicated beyond rows of shapes. We also looked at other ways we can encrypt the message before displaying it, or ways to alter the visuals to further obfuscate the message. These are still topics that need a bit more research before we can begin implementing them. Additionally, I continued working with Shivani to integrate the CV with the decryption, as well as talking with Caroline about the encryption and how to intergrate it with hardware.

Shivani

This week, I worked with Snigdha on connecting the computer vision and decoding parts together. I did a lot of testing to ensure that the order that the image was scanned was correct and that the colors are easily scanned. During class on Wednesday, I started looking into getting OpenCV set up on the other Raspberry Pi and porting our scanning mechanism there. For next week, I plan on working with Caroline to continue the set up process for the Raspberry Pi and do more testing using that camera to make sure that everything is able to scan.

This week’s main goals were to integrate image scanning with OpenCV, to work on our decoding algorithm, and to get the Raspberry Pi encoding system working. Shivani and Snigdha worked together to get the CV to output data that could easily be processed by the decoding algorithm, which we also developed this week.

Caroline

This week, I set up the first Raspberry Pi with WiFi, git, and javascript libraries. I also installed CUPS to get the Raspberry Pi to work with the HP printer we got, but did not realize that I needed to order a printer cable, so now we are waiting on that. I also got I2C communication working with the LCD screen, and I have the pi running our image encoding system, as well as a button for input. For next week, my goal is to get the system running end-to-end with the button, the screen, the keyboard, and the printer.

Snigdha

This week, I worked on adding randomization and encryption to our encoding algorithm. I did this by varying the selected shapes for a character such that a pattern that requires a 4 edged shape could randomly pick between squares, rectangles, and diamonds, for example. I also added an encryption algorithm that relies on mapping the alphabet to a qwerty pattern to shuffle around the letters of the message. I also spent time this week writing a decoder that took in the results from the CV detection in a CSV format, and processed them to determine the input message. This requires a bit more integration testing with the CV but works with manual unit tests. I also discussed a couple alternative encoding ideas with Shivani regarding encoding the data in an existing image that was not a direct 1-to-1 mapping, taking advantage of the existing attributes in various images. This idea is something that we will look into a bit more after preparing for the midpoint demo.

Shivani

This week’s main goals were to integrate the OpenCV detection with the decoding algorithm. We worked on developing a way to refine the CV to lower the processing time and let it detect multiple elements in parallel so it can send the data quicker. We also discussed a way to reduce overhead and duplication of code between the decoding, encoding, and detection parts by using a common dictionary. For this week, we plan on working to integrate the image scanning with the OpenCV, getting the Raspberry Pi set up with a printer and keyboard, and writing the decoding algorithm.

 

Snigdha

This week, I worked with Shivani to figure out an efficient way to combine the results from the CV algorithm with the decoding algorithm. We decided against doing all the decoding processing in the CV file, and instead agreed to export the information in a CSV that could be read in and decoded on the Raspberry Pi.  With this system in place, I will spend the next week on developing writing decoding functions. I also spoke with her about the ability to detect our most recent encoded pattern and will be working on refining it further by changing the encoding pattern from six shapes to three, and adding a filled/unfilled feature to the shapes. Lastly, I worked with the team on the Design Document due this Sunday.

Summary

Updated Gantt Chart

Snigdha

This week, I worked on the encoding/decoding algorithm to generate a visual encoding that was less rudimentary and also more visually pleasing. The algorithm incorporates 4 shapes, 4 colors, and ses of 6 shapes to encode each letter. In addition, the algorithm now includes repetition for more accurate decoding. For next week, in addition to working on the design document, I’ll be working with Shivani to further refine this algorithm and also connect the encoding part to the CV.