System and Method for Detecting Text in Real-World Color Images
First Claim
Patent Images
1. A method of detecting text in real-world images comprising:
- dividing an image representing a real-world scene into one or more regions;
feeding the one or more regions into a cascade of classifiers, the cascade comprising a plurality of stages; and
removing regions of the image classified as non-text regions from the cascade prior to completion of the cascade to avoid subsequent processing of the removed regions.
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Abstract
A method and apparatus for detecting text in real-world images comprises calculating a cascade of classifiers, the cascade comprising a plurality of stages, each stage including one or more weak classifiers, the plurality of stages organized to start out with classifiers that are most useful for ruling out non-text regions, and removing regions classified as non-text regions from the cascade prior to completion of the cascade, to further speed up processing.
22 Citations
17 Claims
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1. A method of detecting text in real-world images comprising:
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dividing an image representing a real-world scene into one or more regions; feeding the one or more regions into a cascade of classifiers, the cascade comprising a plurality of stages; and removing regions of the image classified as non-text regions from the cascade prior to completion of the cascade to avoid subsequent processing of the removed regions. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A system for detecting text in real-world images comprising:
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a processor including; a dividing logic to divide an image into one or more regions; a calculating logic to calculate a cascade of classifiers, the cascade comprising a plurality of stages, each stage including one or more weak classifiers, wherein the plurality of stages is organized to start out with classifiers that are most useful for ruling out non-text regions; a feeding logic to feed the one or more regions into the cascade remove non-text image regions logic to remove image regions classified as the non-text regions from the cascade prior to completion of the cascade, to avoid subsequent processing of the removed regions. - View Dependent Claims (14, 15, 16)
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17. A training system to detect text in real-world images comprising a processor including:
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a cascade comprising a plurality of stages, each stage including one or more weak classifiers, wherein the plurality of stages is organized to start out with classifiers that are most useful for ruling out non-text regions; a feed logic to feed training images into the cascade; a comparison logic to compare classifier results to known training image results; and an adapting logic to adapt one or more of; an order of stages in the cascade of classifiers, an order of classifiers in the stages, one or more classifiers confidence level thresholds, and the classifiers by selecting features for each classifier that reduce the number of false positive and false negative detections by a reduced number of tests.
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Specification