License plate distributed review systems and methods
First Claim
1. A system for license plate matching comprising:
- a system interface configured to receive roadside data from a remote device, the roadside data including at least a roadside image of a vehicle license plate that includes a series of characters; and
at least one processor operatively connected to a memory and the system interface, the processor when executing configured to;
partition the roadside image of the vehicle license plate into at least a first segment and a second segment, each of the first segment and the second segment including at least one character of the series of characters,assign at least the first segment to a first crowd source analysis provider and a second crowd source analysis provider, wherein each of the first crowd source analysis provider and the second crowd source analysis provider are configured to recognize at least a first character included within the first segment of the roadside image of the vehicle license plate,assign at least the second segment to at least a third crowd source analysis provider, and wherein the third crowd source analysis provider is configured to recognize a second character included within the second segment,receive and combine the recognition of the first character and the recognition of the second character to provide a reconstruction of the series of characters of the vehicle license plate, andmatch the vehicle license plate with a known vehicle license plate based on the reconstruction of the series of characters.
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Accused Products
Abstract
According to at least one aspect, systems and methods for distributed license plate review, at one or more crowd source analysis provider, are provided. In one example, a system for license plate review includes an interface configured to receive at least a roadside image of a vehicle license plate, and at least one processor configured to partition the roadside image of the vehicle license plate into one or more segments, and assign the one or more segments to one or more crowd source analysis provider, the one or more crowd source analysis provider being configured to review and recognize at least one character of the vehicle license plate included within an individual segment of the roadside image. In an example, the crowd source analysis provider may allow a reviewer to interact with the individual segment and recognize the at least one character within that segment.
15 Citations
13 Claims
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1. A system for license plate matching comprising:
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a system interface configured to receive roadside data from a remote device, the roadside data including at least a roadside image of a vehicle license plate that includes a series of characters; and at least one processor operatively connected to a memory and the system interface, the processor when executing configured to; partition the roadside image of the vehicle license plate into at least a first segment and a second segment, each of the first segment and the second segment including at least one character of the series of characters, assign at least the first segment to a first crowd source analysis provider and a second crowd source analysis provider, wherein each of the first crowd source analysis provider and the second crowd source analysis provider are configured to recognize at least a first character included within the first segment of the roadside image of the vehicle license plate, assign at least the second segment to at least a third crowd source analysis provider, and wherein the third crowd source analysis provider is configured to recognize a second character included within the second segment, receive and combine the recognition of the first character and the recognition of the second character to provide a reconstruction of the series of characters of the vehicle license plate, and match the vehicle license plate with a known vehicle license plate based on the reconstruction of the series of characters. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A system for license plate matching comprising:
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a system interface configured to receive roadside data from a remote device, the roadside data including at least a roadside image of a vehicle license plate that includes a series of characters; and at least one processor operatively connected to a memory and the system interface, the processor when executing configured to; execute an optical character recognition algorithm; partition the roadside image of the vehicle license plate into one or more segments, each segment of the one or more segments including at least one character of the series of characters, and assign the one or more segments to one or more crowd source analysis provider, the one or more crowd source analysis provider being configured to recognize the at least one character included within an individual segment of the one or more segments of the roadside image of the vehicle license plate, wherein in recognizing the at least one character included within the individual segment, the one or more crowd source analysis provider is configured to confirm at least one character identified by the optical character recognition algorithm.
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9. A method for license plate matching, the method comprising:
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receiving roadside data including at least a roadside image of a vehicle license plate that includes a series of characters; partitioning the roadside image of the vehicle license plate into at least a first segment and a second segment, each of the first segment and the second segment including at least one character of the series of characters; assigning at least the first segment to each of a first crowd source analysis provider and a second crowd source analysis provider; recognizing at least a first character included within the first segment of the roadside image of the vehicle license plate at each of the first crowd source analysis provider and the second crowd source analysis provider; and executing an optical character recognition algorithm to identify individual characters of the series of characters, wherein recognizing the at least first character included within the first segment includes confirming at least one of the individual characters identified by the optical character recognition algorithm. - View Dependent Claims (10, 11, 12, 13)
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Specification