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Hemorrhages in color fundus images usually vary in size and shape, and some are even connected with the retinal vasculature such that they are often omitted by previous detection methods. In this paper, we propose a new method to deal with these problems. During the hemorrhage candidate extraction stage, dark regions and retinal vasculature are segmented out respectively. Their individual advantages...
Human perceptions of music and image are closely related to each other, since both can inspire similar human sensations, such as emotion, motion, and power. This paper aims to explore whether and how music and image can be automatically matched by machines. The main contributions are three aspects. First, we construct a benchmark dataset composed of more than $45\,000$ music-image pairs. Human labelers...
Weak boundary contrast, inhomogeneous background and overlapped intensity distributions of the object and background are main causes that may lead to failure of boundary detection for many traditional active contour methods. In this paper, we propose a region-based active contour model to address these problems in both local and global ways. A localized active contour framework is developed, in which...
Graph cut based on color model is sensitive to statistical information of images. Integrating priority information into graph cut approach, such as the geodesic distance information, may overcome the well-known drawback of bias towards shorter paths that occurred frequently with graph cut methods. In this paper, a conditional random field (CRF) model is formulated to combine color model and geodesic...
Image segmentation plays an important role in computer vision and image analysis. In this paper, we develop a novel algorithm which can automatically segment an image into regions with relative uniform texture or color without the need to decide the region number in advance. In this work, the segmentation is formulated as a labeling problem in the Markov random fields (MRFs) model. An efficient multi-scale...
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