Smile for the Raspberry Pi Powered Photo Booth

[Roo] was tasked with finding a better way to take corporate employee photos. The standard method was for a human resources employee to use a point and shoot camera to take a photo of the new recruits. The problem with this method is many people feel awkward trying to force a smile in front of other people. Plus, if the photo turns out poorly many people won’t ask to have it retaken so as not to feel vain or inconvenience the photographer. [Roo’s] Raspberry Pi powered photo booth solves this problem in a novel way.

The new system has the employee use their own mobile phone to connect to a website running on the Pi. When the employee tells the Pi to snap a photo, the system uses the Raspberry Pi camera module to capture an image. [Roo] actually 3D printed a custom adapter allowing him to replace the standard camera lens if desired. The photo can be displayed on an LCD screen so the user can re-take the photo if they wish.

The system is built into a custom case made from both 3D printed and laser cut parts. The front plate is a frosted white color. [Roo] placed bright white lights behind the front panel in order to act as a flash. The frosted plastic diffuses the light just enough to provide a soft white light for each photo taken. Once the photo is selected, it can then be uploaded to the company database for use with emails, badges, or whatever else.

[Roo] also mentions that the system can easily be changed to send photos via Twitter or other web applications. With that in mind, this system could be a great addition to any hackerspace or event. The code for an older version of the project can be found on the project’s github page.

Continue reading “Smile for the Raspberry Pi Powered Photo Booth”

Pictures that Defeat Key Locks

We’re at LayerOne this weekend and one of the talks we were excited about didn’t disappoint. [Jos Weyers] presented Showing Keys in Public — What Could Possibly Go Wrong? The premise is that pictures of keys, in most cases, are as good as the keys themselves. And that pictures of keys keep getting published.

[Jos] spoke a bit about new services that offer things like 3D scanning and storage of your key for printing when you get locked out, or apps that ask you to take a picture of your key and they’ll mail you a duplicate. Obviously this isn’t the best of ideas; you’re giving away your passwords. And finding a locksmith is easier than findind a 3D printer. But it’s the media gaffs with important keys that intrigues us.

We’ve already seen the proof of concept for taking covert images to perfectly duplicate a key. But these examples are not so covert. One example is a police officer carrying around handcuff keys on a belt clip. Pose for a picture and that key design is now available to all. But news stories about compromised keys are the biggest offenders.

subway-keysA master key for the NYC Subway was compromised and available for sale. The news coverage not only shows a picture at the top of the story of a man holding up the key straight on, but this image of it on a subway map which can be used to determine scale. This key, which is still published openly on the news story linked above, opens 468 doors to the subway system and these are more than just the ones that get you onto the platform for free. We were unable to determine if these locks have been changed, but the sheer number of them has us thinking that it’s unlikely.

firemans-keysWorse, was the availability of fire-department master keys which open lock boxes outside of every building. (Correction: these are fire department keys but not the actual lock-box keys) A locksmith used to cut the original keys went out of business and sold off all their stock. These keys were being sold for $150, which is bad enough. But the news coverage showed each key on a white background, straight on, with annotations of where each type of key will work.

Other examples include video news stories about credit card skimmers installed in gas pumps — that coverage showed the key used to open the pump housing. There was also an example of speed camera control cabinet keys being shown by a reporter.

key-photo-duplication-layerone[Jos’] example of doing the right thing is to use a “prop” key for news stories. Here he is posing with a key after the talk. Unfortunately this is my own house key, but I’m the one taking pictures and I have blurred the teeth for my own security. However, I was shocked during image editing at the quality of the outline in the image — taken at 6000×4000 with no intent to make something that would serve as a source for a copy. It still came out remarkably clear.

Some locks are stronger than others, but they’re all meaningless if we’re giving away the keys.

Incredibly Simple Stage For Product Photos

If you’ve ever tried to take nice photos of small objects in your home, you might have found that it can be more difficult than it seems. One way to really boost the quality of your photos is to get proper lighting with a good background. The problem is setting up a stage for photos can be expensive and time-consuming. [Spafouxx] shows that you don’t need to sink a lot of money or energy into a setup to get some high quality photos.

His lighting setup is very simple. Two wooden frames are built from scraps of wood. The frames stand upright and have two LED strips mounted horizontally. The LEDs face inwards toward the object of the photos. The light is diffused using ordinary parchment paper that you might use when baking.

The frames are angled to face the backdrop. In this case, the backdrop is made of a piece of A4 printer paper propped up against a plastic drink bottle. The paper is curved in such a way to prevent shadows. For being so simple, the example photo shows how clean the images look in the end.

Remote Controlled Wildlife Camera with Raspberry Pi

If you are interested in local wildlife, you may want to consider this wildlife camera project (Google cache). [Arnis] has been using his to film foxes and mice. The core components of this build are a Raspberry Pi and an infrared camera module specifically made for the Pi. The system runs on a 20,000 mAh battery, which [Arnis] claims results in around 18 hours of battery life.

[Arnis] appears to be using a passive infrared (PIR) sensor to detect motion. These sensors work by detecting sudden changes in the amount of ambient infrared radiation. Mammals are good sources of infrared radiation, so the sensor would work well to detect animals in the vicinity. The Pi is also hooked up to a secondary circuit consisting of a relay, a battery, and an infrared light. When it’s dark outside, [Arnis] can enable “night mode” which will turn on the infrared light. This provides some level of night vision for recording the furry critters in low light conditions.

[Arnis] is also using a Bluetooth dongle with the Pi in order to communicate with an Android phone. Using a custom Android app, he is able to connect back to the Pi and start the camera recording script. He can also use the app to sync the time on the Pi or download an updated image from the camera to ensure it is pointed in the right direction. Be sure to check out the demo video below.

If you like these wildlife cameras, you might want to check out some older projects that serve a similar purpose. Continue reading “Remote Controlled Wildlife Camera with Raspberry Pi”

Exposing Private Facebook Photos with a Malicious App

[Laxman] is back again with another hack related to Facebook photos. This hack revolves around the Facebook mobile application’s “sync photos” function. This feature automatically uploads every photo taken on your mobile device to your Facebook account. These photos are automatically marked as private so that only the user can see them. The user would have to manually update the privacy settings on each photo later in order to make them available to friends or the public.

[Laxman] wanted to put these privacy restrictions to the test, so he started poking around the Facebook mobile application. He found that the Facebook app would make an HTTP GET request to a specific URL in order to retrieve the synced photos. This request was performed using a top-level access token. The Facebook server checked this token before sending down the private images. It sounds secure, but [Laxman] found a fatal flaw.

The Facebook server only checked the owner of the token. It did not bother to check which Facebook application was making the request. As long as the app had the “user_photos” permission, it was able to pull down the private photos. This permission is required by many applications as it allows the apps to access the user’s public photos. This vulnerability could have allowed an attacker access to the victim’s private photos by building a malicious application and then tricking victims into installing the app.

At least, that could have been the case if Facebook wasn’t so good about fixing their vulnerabilities. [Laxman] disclosed his finding to Facebook. They had patched the vulnerability less than an hour after acknowledging the disclosure. They also found this vulnerability severe enough to warrant a $10,000 bounty payout to [Laxman]. This is in addition to the $12,500 [Laxman] received last month for a different Facebook photo-related vulnerability.

Caption CERN Contest

To say Hackaday has passionate folks in our comments section would be an understatement. You’ve made us laugh, made us cry, and made us search high and low for the edit button. From the insightful to the humorous, Hackaday’s comments have it all. So, we’re putting you to work helping out an organization that has done incredible work for science over the years.

The European Organization for Nuclear Research (CERN) has quite a storied 60 year history. CERN has been involved in pursuits as varied as the discovery of neutral currents, to Higgs boson research, to the creation of the World Wide Web. Like any research scientists, CERN staff have always been good about documenting their work. Many of these records are in the form of photographs: hundreds of thousands of them. The problem is that no one kept records as to what each photograph depicts!

The folks at CERN are trying to remedy this by publishing over 120,000 unknown photos taken between 1955 and 1985. The hope is that someone out there recognizes the people and equipment in the photos, and can provide some insight as to what exactly we’re looking at.

Here at Hackaday we think these photos should be seen and discussed, and we’re going to have some fun doing it. To that end, we’re hosting the Caption CERN Contest on Each week we’ll add a project log with a new image from CERN’s archives. If you know what the image is, click on CERN’s discussion link for the photo and let them know! If you don’t know, take a shot at a humorous caption. Hackaday staff will pick the best caption each week. Winners will get a shirt from The Hackaday Store.

Here’s how it will work: A new project log will go up every week on Tuesday night at around 9pm PDT. The project log will contain an image from CERN’s archives. You have until the following Tuesday at 9pm PDT to come up with a caption, and drop it in the comments. One entry per user: if you post multiple entries, we’ll only consider the last one.

The first image is up, so head over and start writing those captions!

Good Luck!

A Single Pixel Digital Camera with Arduino

[Jordan] managed to cobble together his own version of a low resolution digital camera using just a few components. The image generated is pretty low resolution and is only in grey scale, but it’s pretty impressive what can be done with some basic hardware.

The heart of the camera is the image sensor. Most consumer digital cameras have tons of tiny receptors all jammed into the sensor. This allows for a larger resolution image, capturing more detail in a smaller space. Unfortunately this also usually means a higher price tag. [Jordan’s] sensor includes just a single pixel. The sensor is really just an infrared photodiode inside of a tube. The diode is connected to an analog input pin on an Arduino. The sensor can be pointed at an object, and the Arduino can sense the brightness of that one point.

In order to compile an actual image, [Jordan] needs to obtain readings of multiple points. Most cameras do this using the large array of pixels. Since [Jordan’s] camera only has a single pixel, he has to move it around and take each reading one at a time. To accomplish this, the Arduino is hooked up to two servo motors. This allows the sensor to be aimed horizontally and vertically. The Arduino slowly scans the sensor in a grid, taking readings along the way. A Processing application then takes each reading and compiles the final image.

Since this camera compiles an image so slowly, it sometimes has a problem with varying brightness. [Jordan] noticed this issue when clouds would pass over while he was taking an image. To fix this problem, he added an ambient light sensor. The Arduino can detect the amount of overall ambient light and then adjust each reading to compensate. He says it’s not perfect but the results are still an improvement. Maybe next time he can try it in color.