Image segmentation using star-convexity constraints
First Claim
1. A computer-implemented method of segmenting an image into a foreground and a background comprising:
- receiving an image to be segmented;
obtaining at least one star center being a location in the image;
using the star center to calculate a geodesic distance map corresponding to the image, the geodesic distance map comprising a geodesic shortest path distance from each image element of the image to the star center;
specifying an energy function representing a problem of segmenting the image;
using the geodesic distance map, optimizing the energy function to obtain the foreground and background, the energy function incorporating a geodesic star-convexity constraint.
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Abstract
Image segmentation using star-convexity constraints is described. In an example, user input specifies positions of one or more star centers in a foreground to be segmented from a background of an image. In embodiments, an energy function is used to express the problem of segmenting the image and that energy function incorporates a star-convexity constraint which limits the number of possible solutions. For example, the star-convexity constraint may be that, for any point p inside the foreground, all points on a shortest path (which may be geodesic or Euclidean) between the nearest star center and p also lie inside the foreground. In some examples continuous star centers such as lines are used. In embodiments a user may iteratively edit the star centers by adding brush strokes to the image in order to progressively change the star-convexity constraints and obtain an accurate segmentation.
197 Citations
20 Claims
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1. A computer-implemented method of segmenting an image into a foreground and a background comprising:
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receiving an image to be segmented; obtaining at least one star center being a location in the image; using the star center to calculate a geodesic distance map corresponding to the image, the geodesic distance map comprising a geodesic shortest path distance from each image element of the image to the star center; specifying an energy function representing a problem of segmenting the image; using the geodesic distance map, optimizing the energy function to obtain the foreground and background, the energy function incorporating a geodesic star-convexity constraint. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A computer-implemented method of segmenting an image into a foreground and a background comprising:
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storing an image to be segmented in memory; obtaining a plurality of star centers each being a location in the image; arranging a processor to specify an energy function representing a problem of segmenting the image, the energy function incorporating a star-convexity constraint based on the plurality of star centers; using the processor to optimize the energy function to obtain the foreground and background. - View Dependent Claims (13, 14, 15)
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16. An image segmentation apparatus comprising:
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a memory arranged to store an image to be segmented at least into a foreground and a background; an input arranged to obtain a plurality of star centers each being a location in the image; a processor arranged to use the star centers to calculate a geodesic distance map corresponding to the image, the geodesic distance map comprising a geodesic shortest path distance from each image element of the image to a nearest one of the star centers; the processor being arranged to specify an energy function representing a problem of segmenting the image; the processor being arranged to use the geodesic distance map to optimize a cost function and obtain the foreground and the background, the cost function incorporating a geodesic star-convexity constraint which is that, for any point p inside the foreground, all points on a geodesic shortest path between the nearest star center and p also lie inside the foreground. - View Dependent Claims (17, 18, 19, 20)
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Specification