September 9, 2011 — Jon McLoone, International Business & Strategic Development
As a change from my usual recreational content, today I thought I would describe a real Mathematica application that I wrote. The project came from my most important Mathematica user—not because she spends a lot of money with Wolfram Research, but because I am married to her!
Her company, Particle Therapeutics, works on needle-free injection devices that fire powdered drug particles into the skin on a supersonic gas shock wave. She was trying to analyze the penetration characteristics on a test medium by photographing thin slices of a target under a microscope and measuring the locations of the particles.
The problem was that her expensive image processing software was doing a poor job of identifying overlapping particles and gave her no manual override for its mistakes.
Faced with the alternative of holding rulers up to her screen and recording each value by hand, I promised that I could do better in Mathematica, with the added advantage that now her image processing tool would be integrated into her analysis code to go from image file to report document in a single workflow.
June 23, 2011 — Yu-Sung Chang, Technical Communication & Strategy
Creating an interactive app could be a complex and painstaking task. Not with Mathematica. Here I will present how I created a photo booth program in three easy steps—mostly during my lunch breaks.
Step One: Architecture
The application will have four main stages. Stage one: We show live webcam images with different image effects applied (possibly multiple pages of them) as a preview, and let the user choose one. Stage two: The chosen image takes up the window, waiting for the user to click a button. Stage three: Count down. Stage four: Capture an image, apply the effect, and add it in a film strip. Repeat.
February 1, 2011 — Daniel Lichtblau, Scientific Information Group
When last seen in the whereabouts of the Marlborough Maze, I was slinking off stage left, having been upstaged by Jon McCloone and his mix of image processing and graph theory alchemy. In a comment on my post, Jaebum Jung showed similar methods.
Me, I only wanted to compute a bunch of distances from the entrance, then walk the maze. But I was not at that time able to show which was the shortest path, or even to prune off the dead ends. I’m over that lapse now. In this post I will provide brief Mathematica code to take the grid of maze pathway distances that I computed, and get the hopeless paths to melt away. Technically this is referred to as a retraction—not in the sense of an apology, but, rather, topology.
December 21, 2010 — Jon McLoone, International Business & Strategic Development
Regular readers of the Wolfram Blog will have seen that the item that I wrote on solving mazes using morphological image processing was thoroughly beaten by the much smarter and better read, Daniel Lichtblau from our Scientific Information Group in his post “Navigating the Blenheim Maze”.
Always up for a challenge (and feeling a little guilty about the rather hacky and lazy way I tried to deal with loops and multiple paths the first time), I am back for another go.
My first approach with any new problem is to think about the nearest available Mathematica command. In the new Mathematica 8 features is a graph theory command FindShortestPath. That certainly sounds promising.
Mixing image processing and graph theory may sound complicated, but one of the central strengths of Mathematica‘s integrated all-in-one design is that different functionality works together, and in this case it proves to be quite easy.
December 7, 2010 — Daniel Lichtblau, Scientific Information Group
I read Jon McLoone’s recent “aMazeing Image Processing in Mathematica” post with some interest.
It showed how to import an image of a maze, and then use image processing functions in Mathematica (some new to Version 8) to draw paths through the maze. What fun! I then observed, to my dismay, that there was no way to determine a “good” path. Frankly, I was disappointed.
I decided that there must be ways to do this in Mathematica. One approach would involve forming a graph. We would have vertices at points where the maze path forks, and we would make weighted edges from approximated distances between these vertices. New functionality in Mathematica supports these graph methods. Unfortunately I am not yet familiar with it.
November 10, 2010 — Jon McLoone, International Business & Strategic Development
First, I am going to make use of an imminent new Mathematica command CurrentImage, which will import a real-time image from a video device. Let’s get some test images using the webcam on my laptop.
November 3, 2010 — Jon McLoone, International Business & Strategic Development
A little over a mile from the Wolfram Research Europe Ltd. office, where I work, lies Blenheim Palace, which has a rather nice hedge maze. As I was walking around it on the weekend, I remembered a map solving example by Peter Overmann using new image processing features in an upcoming version of Mathematica. I was excited to apply the idea to this real-world example.
The maze is meant to depict a cannon with cannon balls below it and flags and trumpets above.
October 27, 2010 — Andrew Moylan, Technical Communication & Strategy
Practically everything I know about British art history would fit in one BBC documentary—the very BBC documentary I watched a little while ago.
I was intrigued to learn about the The Ambassadors, a sixteenth-century painting by Holbein. Among other things, this painting is famous for containing a human skull hidden in plain sight. Can you see it?
September 1, 2010 — Jon McLoone, International Business & Strategic Development
I have a lot to study at the moment, as I learn how to use the technology that’s in our development pipeline. One of the first features I played with was so much fun I thought I would share it with you. You will be able to efficiently and easily texture map over any 3D image.
Texture mapping has all kinds of practical uses for improving visualization, but the first thing that I thought of was setting fire to a plot…
September 8, 2009 — Doug McClintic, Commercial Account Executive
Are you a die-hard video gamer? Can you spend hours at a time sacrificing sleep to play your favorite real-time action console game? Or maybe you find yourself captivated by the amazing animation found in movies such as Pixar’s latest release, Up. Whatever your form of diversion, have you ever stopped to wonder what makes 3D games so realistic or how Pixar managed to animate thousands of balloons lifting Carl’s house? We at Wolfram Research have the inside scoop—it’s all about the math and physics.