The original steganography technique dates back to 440 BC (according to Wikipedia) when a Greek wrote secret messages on a piece of wood, covered it in wax, and then wrote innocent text on the wax. The term, in general, means hiding a message in something that looks harmless. The LVDO project (and a recent Windows fork) says it is steganography, but we aren’t quite sure it meets the definition. What it does is converts data into a video that you can transfer like any other video. A receiver that knows what LVDO parameters you used to create the video can extract the data (although, apparently, the reproduction is not always completely error-free).
The reason we aren’t sure if this really counts as steganography is that–judging from the example YouTube video (which is not encoded)–the output video looks like snow. It uses a discrete cosine transform to produce patterns. If you are the secret police, you might not know what the message says, but you certainly know it must be something. We’d be more interested in something that encodes data in funny cat videos, for example.
Continue reading “Transfer Data via YouTube”
Since 1998 we’ve been privileged to partake in an arcade game known as Dance Dance Revolution, but before that, way back in the 70’s, was the Simon game. It’s essentially a memory game that asks the player to remember a series of lights and sounds. [Uberdam] decided to get the best of both worlds and mixed the two together creating this giant foot controlled Simon game. (English translation.)
The wood platform that serves as the base of the project was fitted with four capacitive sensors, each one representing a “color” on the Simon game. When a player stomps on a color, a capacitive sensor sends a signal to a relay which in turn notifies the Raspberry Pi brain of the input. The Pi also takes care of showing the player the sequence of colored squares that must be stepped on, and keeps track of a player’s progress on a projector.
This is a pretty good way of showing how a small, tiny computer like the Raspberry Pi can have applications in niche environments while also being a pretty fun game. We all remember Simon as being frustrating, and we can only imagine how jumping around on a wooden box would make it even more exciting. Now, who can build a robot that can beat this version of Simon?
Continue reading “DDR-ing a Simon Game with a Raspberry Pi”
We’ve featured quite a few camera gimbals and steady cams here, but this one stands out. For one, [Daniel Rhyoo] was in his sophomore year when he built it. His 2-axis camera gimbal uses brushless DC motors, and is made out of carbon fiber.
[Daniel] machined the carbon fiber parts on a CNC desktop mill and some hand tools. And he also had to teach himself Solid Works to design it. In his slick DIY guide, he starts off by listing the parts and where to source them from, along with the tools needed. Most gimbals use servos for axis movements, which limits the range and do not provide very smooth motion. Brushless motors overcome these limitations allowing a nice, smooth moving gimbal to be built with a wide range of movement. When [Aleksey Moskalenko] introduced the AlexMos brushless motor controller, [Daniel] ordered it out, and then waited until he could get his hands on the right kind of motors. CAD files for all of the machined parts are available for download (.zip file).
He then goes on to blog his build progress, with ample photos to describe the machining and assembly. He does a couple of nice design choices along the way – like using press-nuts to make assembly and dis-assembly easy, and dismantling one of the motors and replacing its shaft with a custom, longer one instead of using a coupler to extend it. At the end, the result is not only a nice looking, light weight rig, but one that works very well thanks to the motors and controller that he used. Check out the video below to see it in action.
Continue reading “Homemade Camera Stabilizer”
[Cliff] is pushing VGA video out of a microcontroller at 800×600 resolution and 60 frames per second. This microcontroller has no video hardware. Before we get to the technical overview, here’s the very impressive demo.
The microcontroller in question is the STM32F4, a fairly powerful ARM that we’ve seen a lot of use in some pretty interesting applications. We’ve seen 800×600 VGA on the STM32F4 before, with a circles and text demo and the Bitbox console. [Cliff]’s build is much more capable, though; he’s running 800×600 @ 60FPS with an underclocked CPU and most (90%) of the microcontroller’s resources free.
This isn’t just a demo, though; [Cliff] is writing up a complete tutorial for generating VGA on this chip. It begins with an introduction to pushing pixels, and soon he’ll have a walkthrough on timing and his rasterization framework.
Just because [Cliff] has gone through the trouble of putting together these tutorials doesn’t mean you can’t pull out an STM Discovery board and make your own microcontroller video hacks. [Cliff] has an entire library of for graphics to allow others to build snazzy video apps.
A filmmaker friend of [Thomas] mentioned that she would like to display a triptych at the 2015 Venice Art Walk. This is no ordinary triptych with a frame for three pictures – this is a video triptych, with three displays each showing a different video, and everything running in sync. Sounds like a cool engineering challenge, huh?
The electronics used in the build were three Raspberry Pi 2s and a trio of HDMI displays. Power is provided by a 12V, 10A switching supply with 5V stepdown converters for the Pis. The chassis is a bunch of aluminum bars and U channel encased in an extremely well made arts and crafts style frame. So far, nothing out of the ordinary.
Putting three monitors and three Pis in a frame isn’t the hard part of this build; getting three different displays all showing different videos is. For this, [Thomas] networked the Pis through an Ethernet hub, got the videos to play independently on a RAM disk with omxplayer. One of the Raspberry Pis serves as the master, commanding the slaves to start, stop, and rewind the video on cue. According to [Thomas], it’s a somewhat hacky solution with a bunch of sleep statements at the beginning of the script to allow the boot processes to finish. It’s a beautiful build, though, and if you ever need to command multiple monitors to display the same thing, this is how you do it.
If you’re wondering, Cornell is just like every other university in one respect: the grad students are starving, and wherever there is free food, students circle like vultures. The engineering and CS departments have a mailing list alerting people to free food, but a more automated solution was desired. The first web cam ever was used to notify grad students if a coffee pot was full, but Cornell shot down this idea on the basis of privacy concerns.
It’s final project time for [Bruce Land]’s courses, and a project by [Ferian Chen] and [Sean Ogden] solved the privacy concerns of a webcam in a kitchen. It’s a real-time video anonymizer, that can also be used to livestream ransom demands if you’re so inclined.
There are actually two parts to this project. The first part pixellates faces and any other skin tone, just like you’d see on a true crime TV show. This part of the project was based on an FPGA-based face detection project. ‘Skin’ pixels are defined as having a difference between the red and green channels within a certain range. With the right lighting, it works very well.
You can identify someone with their voice, too, so [Ferian] and [Sean] also made efforts to disguise hungry student’s voices as well. This was done with a phase vocoder that changes the pitch of someone’s voice, but not the spectral characteristics. The result should have been an audio channel that can’t be pinned down to one person, but is still recognizable as speech. The audio processing didn’t work as intended, with noticeable artifacts in the output. There’s still some work to be done, and now that [Ferian] and [Sean] aren’t checking the kitchen every ten minutes, the might have the time to do it.
It’s graduation time, and you know what that means! Another great round of senior design projects doing things that are usually pretty unique. [Bruce Land] sent in a great one from Cornell where the students have been working on a project that uses FPGAs and a few video cameras to keep score of a ping-pong game.
The system works by processing a live NTSC feed of a ping pong game. The ball is painted a particular color to aid in detection, and the FPGAs that process the video can keep track of where the net is, how many times the ball bounces, and if the ball has been hit by a player. With all of this information, the system can keep track of the score of the game, which is displayed on a monitor near the table. Now, the players are free to concentrate on their game and don’t have to worry about keeping score!
This is a pretty impressive demonstration of FPGAs and video processing that has applications beyond just ping pong. What would you use it for? It’s always interesting to see what students are working on; core concepts from these experiments tend to make their way into their professional lives later on. Maybe they’ll even take this project to the next level and build an actual real, working ping pong robot to work with their scoring system!
Continue reading “FPGAs Keep Track of your Ping Pong Game”