Methods and systems for identifying text in digital images
First Claim
Patent Images
1. A method for identifying text in a digital image, said method comprising:
- a) in an image processing system comprising at least one computing device, expanding a support region of a candidate text pixel in a text-candidate map, wherein said expanding comprises;
i) receiving an edge map wherein said edge map identifies edges in said digital image;
ii) generating an edge count wherein said edge count generating comprises associating an entry in said edge count with a neighborhood in said edge map and the value of said entry in said edge count is the sum of the edge pixels in said neighborhood in said edge map;
iii) receiving a text-candidate map wherein said text-candidate map identifies text-candidate pixels in said digital image; and
iv) generating a text count wherein said text count generating comprises an entry in said text count with a neighborhood in said text-candidate map and the value of said entry in said text count is the sum of the text-candidate pixels in said neighborhood in said text-candidate map,thereby producing a revised text-candidate map;
b) in said image processing system, discriminating pictorial regions in said digital image based on an entropy measure comprising masking using said revised text-candidate map; and
c) in said image processing system, refining said revised text-candidate map based on said pictorial regions.
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Abstract
Aspects of the present invention relate to systems, methods and devices for detection of text in an image using an initial text classification result and a verification process. In particular, a support region of a candidate text pixel in a text-candidate map may be expanded to produce a revised text-candidate map. Pictorial regions in the image may be discriminated based on an entropy measure using masking and the revised text-candidate map, and the revised text-candidate map may be refined based on the pictorial regions.
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Citations
9 Claims
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1. A method for identifying text in a digital image, said method comprising:
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a) in an image processing system comprising at least one computing device, expanding a support region of a candidate text pixel in a text-candidate map, wherein said expanding comprises; i) receiving an edge map wherein said edge map identifies edges in said digital image; ii) generating an edge count wherein said edge count generating comprises associating an entry in said edge count with a neighborhood in said edge map and the value of said entry in said edge count is the sum of the edge pixels in said neighborhood in said edge map; iii) receiving a text-candidate map wherein said text-candidate map identifies text-candidate pixels in said digital image; and iv) generating a text count wherein said text count generating comprises an entry in said text count with a neighborhood in said text-candidate map and the value of said entry in said text count is the sum of the text-candidate pixels in said neighborhood in said text-candidate map, thereby producing a revised text-candidate map; b) in said image processing system, discriminating pictorial regions in said digital image based on an entropy measure comprising masking using said revised text-candidate map; and c) in said image processing system, refining said revised text-candidate map based on said pictorial regions. - View Dependent Claims (2, 3, 4)
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5. A system for identifying text in a digital image, said system comprising:
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a) an expander processor for expanding a support region of a candidate text pixel in a text-candidate map, wherein said expander processor comprises; i) an edge map receiver for receiving an edge map wherein said edge map identifies edges in said digital image; ii) an edge count generator for generating an edge count wherein said edge count generating comprises associating an entry in said edge count with a neighborhood in said edge map and the value of said entry in said edge count is the sum of the edge pixels in said neighborhood in said edge map; iii) a text-candidate map receiver for receiving a text-candidate map wherein said text-candidate map identifies text-candidate pixels in said digital image; and iv) a text count generator for generating a text count wherein said text count generating comprises associating an entry in said text count with a neighborhood in said text-candidate map and the value of said entry in said text count is the sum of the text-candidate pixels in said neighborhood in said text-candidate map, thereby producing a revised text-candidate map; b) a discriminator processor for discriminating pictorial regions in said digital image based on an entropy measure comprising masking using said revised text-candidate map; and c) a refiner processor for refining said revised text-candidate map based on said pictorial regions. - View Dependent Claims (6, 7, 8, 9)
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Specification