Prize winning class team project for improved image processing
The project entails investigating a recent paper and both reproducing and extending the research.
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:
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: