Image processing based on visual attention and reduced search based generated regions of interest
First Claim
1. An approach for reducing complexity of digitized images by using visual attention, comprising:
- determining a gradient image of an input image;
determining a YUV image of the input image;
evaluating gradient pixels of the gradient image;
processing the gradient pixels having values meeting an adaptive threshold;
evaluating Y-channel pixels of the YUV image as contrast pixels;
processing contrast pixels having values meeting an adaptive threshold; and
merging processed gradient and contrast pixels into an output image.
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Abstract
A system for complexity reduction in images involving concepts of visual attention based most probable region detection for object presence and perspective-view based reduced scale-search approaches. Visual attention concept in context uses gradient and contrast of an image. A pixel meeting certain criteria for gradient or contrast values may be further processed for object presence. Limiting image processing to such regions may reduce the complexity of digitized images. Post processing the outcome using morphological operations like dilation and erosion appropriately may help retain some of the missed object pixels in the resultant image. Typically image blocks at different scales are searched for object presence. Reduced-scale search involves removing certain scales during search. As object size in image varies with its location scales within a given scale-range if searched, may lead to higher chances of object presence. This is implemented using relative heights and widths estimation using the perspective view concept.
20 Citations
12 Claims
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1. An approach for reducing complexity of digitized images by using visual attention, comprising:
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determining a gradient image of an input image; determining a YUV image of the input image; evaluating gradient pixels of the gradient image; processing the gradient pixels having values meeting an adaptive threshold; evaluating Y-channel pixels of the YUV image as contrast pixels; processing contrast pixels having values meeting an adaptive threshold; and merging processed gradient and contrast pixels into an output image. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A system for reducing complexity of digital images, comprising:
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an image source module; a gradient pixel selection module connected to the image source module; a contrast pixel selection module connected to the image source module; and a pixel merger module connected to the gradient pixel selection module and to the contrast pixel selection module; and wherein; the gradient pixel selection module comprises a gradient detector connected to the image source module and a gradient pixel evaluator connected to the gradient pixel selection module and the pixel merger module, the gradient pixel evaluator finding minimum and maximum values, and selecting a scale factor for a gradient of an image; and if a gradient pixel has a value less than a product of a scale factor and the minimum value or greater than a product of the scale factor and the maximum value, then the gradient pixel is processed as part of an output image; and
if the gradient pixel does not have a value less than a product of the scale factor and the minimum value or greater than a product of the scale factor and the maximum value, then the gradient pixel is not processed as part of an output image. - View Dependent Claims (9, 10)
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11. A system for reducing complexity of digital images, comprising:
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an image source module; a gradient pixel selection module connected to the image source module; a contrast pixel selection module connected to the image source module; and a pixel merger module connected to the gradient pixel selection module and to the contrast pixel selection module; wherein the gradient pixel selection module comprises a gradient detector connected to the image source module and a gradient pixel evaluator connected to the gradient pixel selection module and the pixel merger module; and wherein the contrast pixel evaluator finds a mean, a standard deviation and selects a multiplication factor for a Y-channel image. - View Dependent Claims (12)
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Specification