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.

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.