The source code for the Tesseract OCR for iPhone project has been published. It’s really simple – more of a skeleton, proof-of-concept project than anything else. Still, though, it’s neat to have nearly point-and-shoot text conversion in your pocket.

The project page is: Pocket OCR

The source code is available at github: http://github.com/rcarlsen/Pocket-OCR

There is certainly a lot of improvement to be made. Automatic color correction. Page layout recognition. Perspective correction…the list could go on. The code is there, so…fork away!

(the thumbnail is a bit tongue-in-cheek…but honest. good conversion requires a good source image: well-lit, macro, focused and tightly cropped seems best)

The 2009 ITP Winter Show is Sunday and Monday, December 20–21. The first visualization of my ongoing bicycle data logging project is on display under the title “seismi{c}ycling“.

This visualization traces the routes I rode throughout the fall, highlighting big bumps. Areas of New York which caused me to experience lots of bumps begin to glow bright red.

The show is a great time; I’d highly suggest coming to see the myriad of projects this year. There’s a online guest book with project map at ITPGuestbook.

Update: Source code for demo project released.

i finally got around to building a proof of concept implementation of tesseract-ocr for the iPhone. months ago, i documented the steps which helped to get the library cross-compiled for the iPhone’s ARM processor, and how to build a fat library for use with the simulator as well. several folks have helped immensely in noting how to actually run the engine in obj-c++. thanks to everyone who has commented so far.

anyway, below is a short video of the POC in action. the basic workflow is: select image from photo library or camera, crop tightly on the box of text you’d like to convert, wait while it processes, select / copy or email text. Read the rest of this entry »

[written for Media Economics & Participation at ITP]

Slashdot users are seeking karma. However, gaining positive karma at Slashdot is just a means to an end; Slashdot users are seeking (limited) power and status among their peers in the form of fleeting moderator access for the vibrant comments component of the highly active, technology-focused news aggregation site. Moderators are chosen from among the registered users using a somewhat obscure algorithm which incorporates each user’s karma rating (a scale of Terrible, Bad, Neutral, Positive, Good, and Excellent), length of membership and randomness. Selected moderators are given special status and 5 mod{eration} points with an expiration window of three days. The moderation status ends when the points have been used in the act of moderating comments or have expired.

The moderation system has been borne out of necessity as the Slashdot community has grown large, bringing the signal-to-noise ratio down and decreasing the satisfaction in reading the raw comment threads. “Flamebait” and “trolls” contribute little more than instigation for starting arguments and fights among the users with typically strong opinions on matters which usually appear on Slashdot. Rob Malda, founder of Slashdot, explains this phenomenon on the Slashdot FAQ: Read the rest of this entry »

Initial presentation of my final project for the Rest of You class at ITP.

I’m logging forces experienced by a bicycle {rider} when traveling through an urban environment. Many of these forces go unnoticed by the rider focused in the action of riding.

I’m looking to utilize mobile GPS-enabled handsets as a central part of the sensor platform to take advantage of their increasing ubiquity and a natural tendency for riders to carry a handset at all times. External sensors and hardware may be connected to these handsets to measure specific metrics, such as light and sound levels, air quality, proximity, heart rate, stress, breathing, work, attitude, speed and vibration.

after a couple of late nights, i have a proof-of-concept in the real-time cycling-related datalogging. the reasons behind the project are still getting sorted, but lately my interest in ubiquitous urban sensor networks has been piqued and this is a tentative exploration in that area. sensors don’t have to remain static as part of physical infrastructure…millions of people are carrying millions of sensors around with them daily. Read the rest of this entry »

This tutorial describes how to set up Eclipse for Arduino (AVR) C/C++ development. Eclipse is a full-featured Integrated Development Environment with modern editor features such as syntax highlighting, code completion and error checking. I became interested in using Eclipse for Arduino development as I’m often simultaneously developing firmware for the chip and visualization software in a Java / Processing applet. Since I’m already using Eclipse for Java / Processing, it’s nice to be able to work in the same environment for both.

The Arduino site has a decent walkthrough, but I found some of the steps to be confusing or outdated. Hopefully, this will get you up and running quickly. Read the rest of this entry »

For the 1-in-1 Project as part of ITP’s 30th anniversary celebration I over-engineering the simple bicycle blinky light. Why go for a simple, off-the-shelf blinky light when we can build a much more complicated one ourselves?!

I’m creating an animated display, which changes to solid red while braking.

Update: (5:26) It’s been a long night, but it all came together. I wish I could have finished at the floor, but sometimes you need to go to your cave. The bike blinky light is all I could have asked for…it’s obnoxious, it’s animated, it has a handlebar control to switch to a flashing warning mode. Read the rest of this entry »

(note: I’m awaiting the HR sensor, this is mostly outward forces)

I’m logging the acceleration forces at the handlebars of my bicycle while riding through New York City. The body has roughly three contact points with a bicycle, the hands at the handlebars, the “seat” at the saddle, and the feet at the pedals. The downward force of the rider’s weight and pedaling force and the upward forces of the bicycle rolling over uneven ground are distributed over these three points. I was interested to see just what kind of forces are “pushing back” that I may not be aware of, myself lost in the act of simply keeping the bicycle upright and safely navigating through traffic.

To contextualize the raw accelerometer data I also tracking GPS location and eventually geocoding the raw data in software. The bicycle sensors are being transmitted via Bluetooth to a mobile phone and the data is logged with a custom written (but now open-source!) python script. Below is the first draft of the visualization. Read the rest of this entry »

This is just a teaser for a project I’ve recently begun, but I had an “a-ha” moment when the visualization program finally came together just now and wanted to share…

This is geocoded accelerometer data from the handlebars of my bicycle on my commute from Greenpoint to ITP in the East Village. The sample at middle of the graph, and the red circle on the path coincide. I realized just now that this is a seam in the Williamsburg Bridge. Neat.

I’ll post proper documentation of the project as it becomes more robust…but I’m excited. Waiting for the heart rate monitor interface to arrive…looking to couple internal status with external events…