Sophomore Kevin Dickey has set an ambitious summer goal of creating an inexpensive, hand-held material classifier, or “gloss meter,” initially hoping to use LEDs (light-emitting diodes) as sensors. In his research, the sophomore from Peoria, Illinois has taken on the life of an imaging scientist and truly embraced the scientific method. Dickey has researched, ordered, and tested LEDs, graphed their performance, and written up pages and pages of data and results concerning the ins and outs of using the devices as sensors. (You can follow Dickey’s progress at http://led-brdf.wikispaces.com.)
Dickey is building an inexpensive version of a device normally costing around $5,000 that will classify the surface gloss of, for example, a countertop or a wall. Dickey envisions a hemispherical device armed with LEDs to sense the object and then transmit the information to a software program that will produce a graph describing the material. He has tried white LEDs, red LEDs, expensive and inexpensive models. His original purchase of several low quality LEDs at Radio Shack actually yielded good results, but two identical LEDs could not sense each other’s specific wavelength of light, a critical criterion for Dickey’s instrument. In other words, the LEDs worked perfectly for the average consumer, but not for an undergraduate researcher.
In the process, however, Dickey has learned the basics of circuitry and refined his knowledge of coding, and he is communicating his progress on a daily basis. Most recently, Dickey realized that because modern LEDs are now used so commonly in all kinds of lighting , there is no need for them to function well as sensors. Instead, Dickey says, he has decided to turn to phototransistors, which are inexpensive, fast, and similar in size to LEDs. “The physical dimensions are especially important because a sensor that is round and shaped like an LED will allow for easier mounting within the final gloss measurement device,” Dickey says. “I’m currently testing a new set of phototransistors as we speak, expecting some good results. They are, after all, designed to sense light!” There is hope, after all, for Dickey’s inexpensive material classifier.
Chen—a double major in Management Information Systems and Imaging Science from Shenzen, China—received $3,000 in support from the Summer Honors Program to design a system that solves the problem of false exposure in digital cameras. This adaptive, programmable camera system allows Chen to control the shutter of the camera at the level of an individual pixel with the goal of producing more detailed images and, eventually, improved color. Most conventional digital cameras with a single aperture have limited dynamic range, which makes it difficult to preserve the same details in the bright and dark areas of a potential shot. In order to capture high dynamic range (HDR) images, current technology forces photographers to shoot multiple images of the same subject. And, if the subject is moving, this method doesn’t even work. To explore new methods, Chen is using an LCD monitor without a backlight to control the transparency of each pixel. Chen has used the program MATLAB to create a code in which each pixel has a unique exposure. Chen’s software program will give him the ability to increase the amount of light that is hitting an underexposed area on the sensor, while blocking light on an overexposed area, thereby preserving details in both bright and darks areas of the image. His system is now a working prototype, complete with a platform for the LCD modulator built from LEGO bricks.
“The future goal of this system is to enhance the color range of the camera,” Chen says. He plans to continue this work as his senior project. Will we see this technology at Best Buy in the next five years? “It's hard to say,” Chen says. “It usually takes years for new technologies to go from lab to market. We will try our best."
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