Cheap And Reliable Portable Face Recognition System

faceaccess_portable_facial_recognition

For their senior ECE 4760 project, engineering students [Brian Harding and Cat Jubinski] put together a pretty impressive portable face recognition system called FaceAccess. The system relies on the eigenface method to help distinguish one user from another, a process that the pair carried out using MatLab.

They say that the system only needs to be hooked up to a computer once, during the training period. It is during this period that faces are scanned and processed in MatLab to create the eigenface set, which is then uploaded to the scanner.

Once programmed, the scanner operates independently of the computer, powered by its own ATmega644 micro controller. Users enroll their face by pressing one button on the system, storing their identity as a combination of eigenfaces in the onboard flash chip. Once an individual has been enrolled, a second button can be pressed to gain access to whatever resources the face recognition system is protecting.

The students say that their system is accurate 88% of the time, with zero false positives – that’s pretty impressive considering the system’s portability and cost.

Stick around to see a quick demo video of their FaceAccess system in action.

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Webcam Images Processed And Played Back On LED Display

[Mathieu] has bee working to refine the code running on an LED matrix, and added some neat display tricks along the way. He wanted to make the display directly addressable from a computer. The 96×64 bi-color LED display is powered by an Atmel FPSLIC and already used double-buffering. Enabling a PC to write directly to one of the buffers was not too hard, requiring just a bit of optimization to get the timing right. From the look of the video after the break, he nailed it.

The video feed is generated from a webcam stream using Matlab to process each image. Just 50 lines of code captures a frame, sizes it appropriately, converts the result to black and white for edge detection, then finishes the job by compressing image data for transmission to the embedded processor. We’d like to say it’s easier that it sounds but we’re pretty impressed with this work. The display manages about 42 Hz with the current setup.

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Midi Gloves

We’re being inundated with glove-based peripheral hacks. This is another final project from Cornell, keyboard out of the equation by adding 8 piezo sensors to a pair of gloves thereby shunning the pinky finger. We like this one because it’s easy to build and the midi interface implementation is well documented if you want to build your own.

As you can see after the break, this is easy to use with music software like Garage Band because it is a standard MIDI device. In addition, a MATLAB interface allows for custom mapping in case you want to change what each finger does.

We remember our first introduction to glove-based performances with Tod Machover’s Bug Mudra many years ago. We hope the music input hacks we’re seeing will lead to a whole new generation of music innovators.

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HOPE 2008: The Impossibility Of Hardware Obfuscation


The Last HOPE is off and running in NYC. [Karsten Nohl] started the day by presenting The (Im)possibility of Hardware Obfuscation. [Karsten] is well versed in this subject having worked on a team that the broke the MiFare crypto1 RFID chip. The algorithm used is proprietary so part of their investigation was looking directly at the hardware. As [bunnie] mentioned in his Toorcon silicon hacking talk, silicon is hard to design even before considering security, it must obey the laws of physics (everything the hardware does has to be physically built), and in the manufacturing process the chip is reverse engineered to verify it. All of these elements make it very interesting for hackers. For the MiFare crack, they shaved off layers of silicon and photographed them. Using Matlab they visually identified the various gates and looked for crypto like parts. If you’re interested in what these logic cells look like, [Karsten] has assembled The Silicon Zoo. The Zoo has pictures of standard cells like inverters, buffers, latches, flip-flops, etc. Have a look at [Chris Tarnovsky]’s work to learn about how he processes smart cards or [nico]’s guide to exposing standard chips we covered earlier in the week.