Automatic correction of skew in natural images and video
First Claim
1. A method to correct skew in an image of a scene of real world, the method comprising:
- automatically selecting a subset of first regions by filtering out second regions, from among a set of regions identified in the image, at least based on one or more attributes related to geometry of the regions;
automatically determining a plurality of candidate angles of skew, at least based on pixels in a particular region in the subset of first regions;
automatically identifying as an angle of skew of the image, a most common candidate angle among the plurality of candidate angles; and
automatically rotating by negative of the angle of skew of the image, at least the subset of first regions;
wherein the automatically selecting, the automatically determining, the automatically identifying and the automatically rotating are performed by at least one processor.
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Abstract
An electronic device and method use a camera to capture an image of an environment outside followed by identification of regions therein. A subset of the regions is selected, based on attributes of the regions, such as aspect ratio, height, and variance in stroke width. Next, a number of angles that are candidates for use as skew of the image are determined (e.g. one angle is selected for each region. based on peakiness of a histogram of the region, evaluated at different angles). Then, an angle that is most common among these candidates is identified as the angle of skew of the image. The just-described identification of skew angle is performed prior to classification of any region as text or non-text. After skew identification, at least all regions in the subset are rotated by negative of the skew angle, to obtain skew-corrected regions for use in optical character recognition.
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Citations
25 Claims
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1. A method to correct skew in an image of a scene of real world, the method comprising:
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automatically selecting a subset of first regions by filtering out second regions, from among a set of regions identified in the image, at least based on one or more attributes related to geometry of the regions; automatically determining a plurality of candidate angles of skew, at least based on pixels in a particular region in the subset of first regions; automatically identifying as an angle of skew of the image, a most common candidate angle among the plurality of candidate angles; and automatically rotating by negative of the angle of skew of the image, at least the subset of first regions; wherein the automatically selecting, the automatically determining, the automatically identifying and the automatically rotating are performed by at least one processor. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. At least one non-transitory computer readable storage media comprising a plurality of instructions to be executed by at least one processor to correct skew in an image of a scene of real world, the plurality of instructions comprising:
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first instructions to select a subset of first regions by filtering out second regions, from among a set of regions identified in the image, at least based on one or more attributes related to geometry of the regions; second instructions to determine a plurality of candidate angles of skew, at least based on pixels in a particular region in the subset of first regions; third instructions to identify as an angle of skew of the image, a most common candidate angle among the plurality of candidate angles; and fourth instructions to rotate by negative of the angle of skew of the image, at least the subset of first regions. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
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17. A mobile device to decode text in real world images, the mobile device comprising:
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a camera; a memory operatively connected to the camera to receive at least an image therefrom, the image comprising one or more text regions; at least one processor operatively connected to the memory to execute a plurality of instructions stored in the memory; wherein the plurality of instructions cause the at least one processor to; select a subset of first regions by filtering out second regions, from among a set of regions identified in the image, at least based on one or more attributes related to geometry of the regions; determine a plurality of candidate angles of skew, at least based on of pixels in a particular region in the subset of first regions; identify as an angle of skew of the image, a most common candidate angle among the plurality of candidate angles; and rotate by negative of the angle of skew of the image, at least the subset of first regions. - View Dependent Claims (18, 19, 20, 21, 22, 23, 24)
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25. A mobile device comprising:
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a camera to capture an image of an environment outside the mobile device; a memory coupled to the camera for storing the image; means, coupled to the memory, for identifying a set of regions in the image; wherein each region in the set of regions is identified based on variation of intensities of pixels; means for selecting a subset of first regions by filtering out second regions, from among the set of regions identified in the image, at least based on one or more attributes related to geometry of the regions; means for determining a plurality of candidate angles of skew, at least based on pixels in the a particular region in the subset of first regions; means for identifying as an angle of skew of the image, a most common candidate angle among the plurality of candidate angles, by use of at least one processor; and means for rotating by negative of the angle of skew of the image, at least the subset of first regions.
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Specification