METHODS AND SYSTEMS FOR VEHICLE TAG NUMBER RECOGNITION
First Claim
1. An image-processing method for tag recognition in captured images, said method comprising:
- capturing a side image of a vehicle utilizing at least one camera of an automated vision-based recognition system comprising an image processor;
localizing with said image processor a candidate region from regions of interest with respect to a physical object comprising a tag and a tag number shown in regions of interest within said side image of said vehicle by classifying said side image using a classifier trained as a trained classifier in an offline phase;
calculating with said image processor a plurality of confidence levels with respect to each digit recognized as a result of an optical character recognition operation performed with respect to said tag number;
determining with said image processor optimal candidates within said candidate region for said tag number based on individual character confidence levels among said plurality of confidence levels; and
validating with said image processor said optimal candidates from a pool of valid tag numbers using prior appearance probabilities and returning data indicative of a most probable tag to be detected to improve image recognition accuracy with respect to data representing said physical object comprising said tag and tag number.
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Accused Products
Abstract
Methods and systems for tag recognition in captured images. A candidate region can be localized from regions of interest with respect to a tag and a tag number shown in the regions of interest within a side image of a vehicle. A number of confidence levels can then be calculated with respect to each digit recognized as a result of an optical character recognition operation performed with respect to the tag number. Optimal candidates within the candidate region can be determined for the tag number based on individual character confidence levels among the confidence levels. Optimal candidates from a pool of valid tag numbers can then be validated using prior appearance probabilities and data returned, which is indicative of the most probable tag to be detected to improve image recognition accuracy.
14 Citations
22 Claims
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1. An image-processing method for tag recognition in captured images, said method comprising:
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capturing a side image of a vehicle utilizing at least one camera of an automated vision-based recognition system comprising an image processor; localizing with said image processor a candidate region from regions of interest with respect to a physical object comprising a tag and a tag number shown in regions of interest within said side image of said vehicle by classifying said side image using a classifier trained as a trained classifier in an offline phase; calculating with said image processor a plurality of confidence levels with respect to each digit recognized as a result of an optical character recognition operation performed with respect to said tag number; determining with said image processor optimal candidates within said candidate region for said tag number based on individual character confidence levels among said plurality of confidence levels; and validating with said image processor said optimal candidates from a pool of valid tag numbers using prior appearance probabilities and returning data indicative of a most probable tag to be detected to improve image recognition accuracy with respect to data representing said physical object comprising said tag and tag number. - View Dependent Claims (2, 3, 5, 6, 7, 8, 9, 10, 12, 13)
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4. (canceled)
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11. An image-processing system for tag recognition in captured images, said system comprising:
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at least one camera of an automated vision-based recognition system, a processor that communicates with said at least one camera; and a computer-usable medium embodying computer program code, said computer-usable medium capable of communicating with the processor, said computer program code comprising instructions executable by said processor and configured for; capturing a side image of a vehicle utilizing at least one camera of an automated vision-based recognition system; localizing a candidate region from regions of interest with respect to a physical object comprising a tag and a tag number shown in regions of interest within said side image of said vehicle captured by said at least one camera by classifying said side image using a classifier trained as a trained classifier in an offline phase; calculating a plurality of confidence levels with respect to each digit recognized as a result of an optical character recognition operation performed with respect to said tag number; determining optimal candidates within said candidate region for said tag number based on individual character confidence levels among said plurality of confidence levels; and validating said optimal candidates from a pool of valid tag numbers using prior appearance probabilities and returning data indicative of a most probable tag to be detected to improve image recognition accuracy with respect to data representing said physical object comprising said tag and tag number. - View Dependent Claims (15, 16, 17, 18)
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14. (canceled)
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19. A non-transitory processor-readable medium storing code representing instructions to cause a process for tag recognition in captured images, said code comprising code to:
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capture a side image of a vehicle utilizing at least one camera of an automated vision-based recognition system comprising an image processor; localize a candidate region from regions of interest with respect to a physical object comprising a tag and a tag number shown in regions of interest within said side image of said vehicle by classifying said side image using a classifier trained as a trained classifier in an offline phase; calculate a plurality of confidence levels with respect to each digit recognized as a result of an optical character recognition operation performed with respect to said tag number; determine optimal candidates within said candidate region for said tag number based on individual character confidence levels among said plurality of confidence levels; and validate said optimal candidates from a pool of valid tag numbers using prior appearance probabilities and returning data indicative of a most probable tag to be detected to improve image recognition accuracy with respect to data representing said physical object comprising said tag and tag number. - View Dependent Claims (20, 21, 22)
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Specification