Image segmentation
OwnerLulu He, Feng Tang +1inventors
InventorsLulu He, Feng Tang, Qian Lin
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Abstract
In one implementation, an image segmentation system defines a first discriminative classifier and a second discriminative classifier. The first discriminative classifier is associated with a first segment of an object in an image based on a first foreground sample region of the image and a first background sample region of the image. The second discriminative classifier is associated with a second segment of the object based on a second foreground sample region of the image and a second background sample region of the image. The image segmentation system then identifies at least a portion of the first segment using the first discriminative classifier and at least a portion of the second segment using the second discriminative classifier.
Claims20
An image segmentation method, comprising:
- defining a first discriminative classifier associated with a first segment of an object in an image based on a first foreground sample region of the image and a first background sample region of the image;
- defining a second discriminative classifier associated with a second segment of the object based on a second foreground sample region of the image and a second background sample region of the image;
- identifying at least a portion of the first segment using the first discriminative classifier;
- and
- identifying at least a portion of the second segment using the second discriminative classifier.
An image segmentation system, comprising:
- a sample engine to select, independent of user input, a first foreground sample region of the image, a first background sample region of the image, a second foreground sample region of the image, and a second background sample region of the image;
- a descriptor module to define a plurality of descriptors associated with the first foreground sample region, a plurality of descriptors associated with the first background sample region, a plurality of descriptors associated with the second foreground sample region, and a plurality of descriptors associated with the second background sample region;
- a discriminative classifier generator to define a first discriminative classifier associated with a first segment of an object in the image and a second discriminative classifier associated with a second segment of the object,
- the first discriminative classifier based on the plurality of descriptors associated with the first foreground sample region and the plurality of descriptors associated with the first background sample region,
- the second discriminative classifier based on the plurality of descriptors associated with the second foreground sample region and the plurality of descriptors associated with the second background sample region.
A processor-readable medium, comprising code representing instructions that when executed at a processor cause the processor to:
- identify a reference segment of an object within an image;
- select, independent of user input, a first foreground sample region of the image and a first background sample region of the image, the first foreground sample region selected based on at least one of a size of the reference segment, a location of the reference segment, an orientation of the reference segment, or a combination thereof;
- select, independent of user input, a second foreground sample region of the image and a second background sample region of the image;
- define a first discriminative classifier based on the first foreground sample region and the first background sample region;
- and
- define a second discriminative classifier based on the second foreground sample region and the second background sample region.
Dependencies are inferred from the claim text.