Date of Award:
Master of Science (MS)
The explosion of internet traffic, advent of social media sites such as Facebook and Twitter, and increased availability of digital cameras has saturated life with images and videos. Never before has it been so important to sift quickly through large amounts of digital information. Salient Object Detection (SOD) is a computer vision topic that finds methods to locate important objects in pictures. SOD has proven to be helpful in numerous applications such as image forgery detection and traffic sign recognition. In this thesis, I outline a novel SOD technique to automatically isolate important objects from the background in images.
Buck, Robert, "Cluster-Based Salient Object Detection Using K-Means Merging and Keypoint Separation with Rectangular Centers" (2016). All Graduate Theses and Dissertations. 4631.
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