Talking about my generation

Oct. 1, 2008
Innovations in machine-vision hardware and software may best be found in unexpected sources and partnerships


Innovations in machine-vision hardware and software may best be found in unexpected sources and partnerships

By Andy Wilson, Editor
[email protected]

On a recent trip to England I was fortunate enough to stay with my brother Dave and his son Paul, who is studying how to program FPGAs at the University of Bristol. As usual, I needed to know about all the books, courses, software programming tools, and development tools he was using in the pursuit of his degree.

During the course of the conversation, Paul mentioned that “on the side” he had coded-up a video game “for a laugh.” As I had performed the same task over 30 years earlier (albeit on an Apple Macintosh II), I was intrigued. The game, it transpired, was a first-level rendition of the popular 30-year-old “Space Invaders”game.

While the idea certainly wasn’t original, the way Paul had coded the game certainly was. In fact, he demonstrated to me “his” version running on a mobile phone. It was a marriage of technologies that surely could not fail to win him many fans (and make lots of money). Unfortunately, being 20 years old, Paul had no idea how to go about licensing, marketing, or selling his idea to the likes of Apple, Nokia, or Motorola.

On my return to the United States, I pondered his conundrum and discovered that this was not a phenomenon faced only by the English. During several Web searches, I discovered a piece of code written by Bradley Ward to generate pseudo 3-D images using a webcam. Those of you interested can view a video of the software running at

Being intrigued, I e-mailed Bradley and asked him how he planned to offer the code. To my horror, the reply was rather simple. It seems that Bradley will supply the code to “anyone interested.” Once again, no licensing, marketing, or sales plan seemed to be in place.

They have an idea

As if things couldn’t get much worse, my recent trip to NI Week drove the final nail into this coffin. At National Instruments’ own booth, Benjamin Cook, an undergraduate student at Rose-Hulman Institute of Technology and part-time NI intern, had developed an FPGA-based software package that emulated a number of different guitar pedal effects such as distortion, ring modulation, and tremolo effects. With the massive sales of Activision’s Guitar Hero on my mind, I asked him if he had thought about plans to embed these effects into such products. He had not, although he was amenable to discussing any ideas with those who approached him.

With so many talented young people and so many good ideas, it is a mighty shame that there is no online brokerage to offer such ideas to manufacturers. So how are poor starving students supposed to make money from their efforts? Some companies involved in machine vision have an idea. Last year, for example, Aqsense, using ideas originally developed at the University of Girona, developed an improved method of determining the center point of reflected laser Gaussian profiles that is more accurate than center-of-gravity-based methods (see “Reading the Shapes,”Vision Systems Design, March 2008, pp. 7-11).

To market, promote, and sell this concept, the company did not embark on a large-scale marketing, advertising, and public relations campaign. Rather, the software was licensed to other camera and software companies with prior experience in structured lighting and machine vision. By tying together with such companies as Photonfocus and Stemmer Imaging, the company can concentrate on product development while at the same time offering its products to many companies worldwide.

At the November VISION 2008 show in Stuttgart, many of these third-party companies will be demonstrating their products with Aqsense software. Other small companies with a good hardware or software product would do well to follow the example set by Aqsense. By leveraging an installed base of products, software and hardware developers-students included-can add value to existing systems while at the same time making money and funding future machine-vision research. Tapping into the next generation of researchers and students will provide a great boon for the machine-vision industry.

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