Analysis of bio-based composites for image segmentation with the aid of games Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/ww72bf91j

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  • A fundamental problem in computer vision is to partition an image into meaningful segments. While image segmentation is required by many applications, the thesis focuses on segmentation of computed tomography (CT) images for analysis and quality control of composite materials. The key research contribution of this thesis is a novel image segmentation framework for including end-users in computation. This represents a departure from the traditional methods, which segment images without considering domain knowledge, and access to user feedback. Given a set of CT images of three different composite materials, we would like to create a database of annotated images for all the regions of interest. The annotated images can be used to check the accuracy of segmentation algorithms. Because of how time consuming and mundane image annotation is for a person to do, we propose to turn this task into a game. The game is aimed at making the annotation task easier, because it engages imagination, creativity, fellowship of all subjects involved. In particular, we are interested in games that can be played on the internet by many people like those in Amazon Turk, so that the broader public can get involved. We create a Game with a Purpose (GWAP) called ESP 2.0 for creating image annotations, and thus enable benchmarking of existing segmentation algorithms on our database.
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