The Michigan Engineer News Center

Prize winning class team project for improved image processing

The project entails investigating a recent paper and both reproducing and extending the research.| Short Read
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IMAGE:  Prof. Jeff Fessler, Madan Ravi Ganesh, Leyou Zhang, Adeline Hong, Farhan Baqai (Apple)

An interdisciplinary team of three graduate students earned prizes (Apple iPad Air2’s) in the graduate level course, EECS 556: Image Processing, thanks to the sponsorship of Apple. The course, taught by Prof. Jeff Fessler, covers the theory and application of digital image processing, which has applications in biomedical images, time-varying imagery, robotics, and optics. Students investigate a recent paper and both reproduce and extend the research.

The winning project, Object boundary detection using decoupled active contours, by Madan Ravi Ganesh (MS student in EE:Systems), Adeline Hong (PhD student in BME), and Leyou Zhang (PhD student in Physics), confirmed the findings of the original paper, Decoupled Active Contour (DAC) for Boundary Detection, Mishra, et al., which focused on the issue of detecting the boundary of the object of interest and its background in a given image.

The algorithm created to accomplish this boundary detection was proven to be superior to existing methods, and is illustrated below:

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IMAGE:  Flow diagram outlining each stage of the DAC algorithm and its corresponding output. Blue pixels indicate aggregation of sampling points after importance sampling.

The Michigan team was able to extend the DAC method to incorporate color information from the images while also enhancing DAC’s performance, as shown below:

Enlargealgorithm comparison
grad students eecs 556
flow diagram of algorithm
algorithm comparison
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Catharine June
ECE Communications and Marketing Manager

Electrical Engineering and Computer Science

(734) 936-2965

3301 EECS

The electrons absorb laser light and set up “momentum combs” (the hills) spanning the energy valleys within the material (the red line). When the electrons have an energy allowed by the quantum mechanical structure of the material—and also touch the edge of the valley—they emit light. This is why some teeth of the combs are bright and some are dark. By measuring the emitted light and precisely locating its source, the research mapped out the energy valleys in a 2D crystal of tungsten diselenide. Credit: Markus Borsch, Quantum Science Theory Lab, University of Michigan.

Mapping quantum structures with light to unlock their capabilities

Rather than installing new “2D” semiconductors in devices to see what they can do, this new method puts them through their paces with lasers and light detectors. | Medium Read