METHOD AND SYSTEM FOR ANALYZING IMAGE IDENTIFICATIONS TO IDENTIFY AN ENTITY
First Claim
1. A method for analyzing image identifications to determine whether the image identifications identify an entity, said method comprising:
- receiving, by a validation engine from at least two optical character recognition (OCR) engines, at least two identification sets such that each identification set comprises a character string consisting of a plurality of characters and a confidence level associated with the character string, wherein each character string has been derived by a respective OCR engine of the at least two OCR engines from an image of the entity, wherein at least one identification set of the at least two identification sets is received by the validation engine from each OCR engine;
comparing, by the validation engine, each character string with every other character string, resulting in identifying all conflicting character strings, wherein any two non-identical character strings are considered to be conflicting;
analyzing, by the validation engine, the confidence level in each identification set, resulting in determining whether said each confidence level exceeds a predefined threshold confidence level;
applying, by the validation engine, at least one rule to the identifying resulting from said comparing and/or to the determining resulting from said analyzing, resulting in ascertaining whether or not the entity has been identified; and
storing, in a data store coupled to the validation engine, an indication of whether or not said ascertaining has ascertained that the entity has been identified, wherein said storing is performed by the validation engine.
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Accused Products
Abstract
A method for analyzing image identifications to determine whether image identifications identify an entity (e.g., license plate of a vehicle). Identification sets are received from at least one optical character recognition (OCR) engine. Each identification set includes a character string and an associated confidence level. Each character string is derived by the respective OCR engine from an image of the entity. An identification set is received from each OCR engine. The character strings are compared, resulting in identifying all conflicting character strings, wherein any two non-identical character strings are considered to be conflicting. The confidence level in each identification set is analyzed, resulting in determining whether each confidence level exceeds a predefined threshold confidence level. At least one rule is applied to the preceding results to ascertain whether or not the entity has been identified. An indication of whether or not the entity has been identified is stored.
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Citations
35 Claims
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1. A method for analyzing image identifications to determine whether the image identifications identify an entity, said method comprising:
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receiving, by a validation engine from at least two optical character recognition (OCR) engines, at least two identification sets such that each identification set comprises a character string consisting of a plurality of characters and a confidence level associated with the character string, wherein each character string has been derived by a respective OCR engine of the at least two OCR engines from an image of the entity, wherein at least one identification set of the at least two identification sets is received by the validation engine from each OCR engine; comparing, by the validation engine, each character string with every other character string, resulting in identifying all conflicting character strings, wherein any two non-identical character strings are considered to be conflicting; analyzing, by the validation engine, the confidence level in each identification set, resulting in determining whether said each confidence level exceeds a predefined threshold confidence level; applying, by the validation engine, at least one rule to the identifying resulting from said comparing and/or to the determining resulting from said analyzing, resulting in ascertaining whether or not the entity has been identified; and storing, in a data store coupled to the validation engine, an indication of whether or not said ascertaining has ascertained that the entity has been identified, wherein said storing is performed by the validation engine. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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16. A method for analyzing image identifications to determine whether the image identifications identify a license plate of a vehicle, said method comprising:
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receiving, by a validation engine from at least one optical character recognition (OCR) engine, at least two identification sets such that each identification set comprises a character string consisting of a plurality of characters and a confidence level associated with the character string, wherein each character string has been derived by a respective OCR engine of the at least one OCR engine from an image of the license plate attached to the front or rear of the vehicle, wherein at least one identification set of the at least two identification sets is received by the validation engine from each OCR engine; comparing, by the validation engine, each character string with every other character string, resulting in identifying all conflicting character strings, wherein any two non-identical character strings are considered to be conflicting; analyzing, by the validation engine, the confidence level in each identification set, resulting in determining whether said each confidence level exceeds a predefined threshold confidence level and/or is within a predefined range of confidence levels; applying, by the validation engine, at least one rule to the identifying resulting from said comparing and/or to the determining resulting from said analyzing, resulting in ascertaining whether or not the license plate has been identified; and storing, in a data store coupled to the validation engine, an indication of whether or not said ascertaining has ascertained that the license plate has been identified, wherein said storing is performed by the validation engine. - View Dependent Claims (17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35)
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Specification