Content aware, spatially adaptive automated thresholding of images
AssigneeAdobe Inc.
InventorsVipul Aggarwal, Naveen Prakash Goel
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Abstract
Techniques are described for obtaining at least one image using at least one processor. The techniques may include selecting a plurality of objects defined by a plurality of pixels within the at least one image. The techniques may include determining perceptual information associated with each of the plurality of objects and generating a context for each of the plurality of pixels that define the plurality of objects. The techniques may also include automatically thresholding the at least one image to generate an output image that represents the at least one image.
Claims17
A computer-implemented method for adaptively thresholding image pixels, the method comprising:
- obtaining at least one image using at least one processor;
- detecting, using the at least one processor, a plurality of objects defined by a plurality of pixels within the at least one image;
- determining, using the at least one processor, perceptual information associated with each of the plurality of objects;
- generating, using the perceptual information, a context for each of the plurality of pixels that define the plurality of objects, wherein generating the context includes generating a saliency map based on a determined Euclidean distance and mean associated with at least a portion of pixels corresponding to a filtered version of the at least one image;
- and
- automatically thresholding, using the context for each respective pixel, the at least one image to generate an output image that represents the at least one image, the output image being a binarized version of the at least one image.
A computer program product embodied on a non-transitory computer-readable storage medium and comprising an introspection network and instructions that, when executed by at least one computing device, is configured to cause the at least one computing device to:
- obtain at least one image using at least one processor;
- detect, using the at least one processor, a plurality of objects defined by a plurality of pixels within the at least one image;
- determine, using the at least one processor, perceptual information associated with each of the plurality of objects;
- generate, using the perceptual information, a context for each of the plurality of pixels that define the plurality of objects, wherein generating the context includes generating a saliency map based on a determined Euclidean distance and mean associated with at least a portion of pixels corresponding to a filtered version of the at least one image;
- and automatically threshold, using the context for each respective pixel, the at least one image to generate an output image that represents the at least one image, the output image being a binarized version of the at least one image.
A system comprising:
- at least one memory including instructions;
- and at least one processor that is operably coupled to the at least one memory and that is arranged and configured to execute instructions that, when executed, cause the at least one processor to:
- receive at least one image;
- and in response to receiving the at least one image, automatically:
- detect a plurality of objects defined by a plurality of pixels within the at least one image;
- determine perceptual information associated with each of the plurality of objects;
- generate, using the perceptual information, a context for each of the plurality of pixels that define the plurality of objects, wherein generating the context includes generating a saliency map based on a determined Euclidean distance and mean associated with at least a portion of pixels corresponding to a filtered version of the at least one image;
- threshold, using the context for each respective pixel, the at least one image to generate an output image that represents the at least one image, the output image being a binarized version of the at least one image;
- and trigger display of the generated output image.
Dependencies are inferred from the claim text.