Image Segmentation Based on Structural Inconsistency

• Main Authors: Lan, Yu-Chien, 藍郁茜
• Other Authors: Lin, I-Chen
• Format: Others
• Language: en_US
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/00476349824421534431

碩士 === 國立交通大學 === 多媒體工程研究所 === 102 === We introduce a novel approach to deal with image segmentation which takes into account the consistent structure of the backgrounds. The concept is from back- ground subtraction. Our method only needs users to specify their target objects by a bounding box. The system then finds the object contour by maximizing the consensus between the predicted background and the original image. We combine principles from image completion and foreground extraction approaches into a powerful unied engine. Besides, a new and harder dataset is introduced with images which have structural background objects.