METHODS AND SYSTEMS FOR ACCURATELY RECOGNIZING VEHICLE LICENSE PLATES
First Claim
1. A license plate detection and recognition (LPDR) system comprising of:
- a processor, a non-transitory storage element coupled to the processor, encoded instructions stored in the non-transitory storage element, wherein the encoded instructions when implemented by the processor, configure the LPDR system to;
receive an image by an image input unit, wherein the image input unit receives the image from at least one of an image capturing device, a network, a computer and a memory unit;
detect one or more regions in the image by a license plate detection unit, wherein a region of the one or more regions includes a license plate, the license plate detection unit further comprising;
a binarization unit configured to generate a set of binarized images of the region using at least one of a multi-scale difference of Gaussian filter and a variable adaptive threshold (T), wherein the variable adaptive threshold (T) is computed based on at least one parameter of a set of parameters computed locally in a window centered at a location in the region; and
a filtration unit configured to remove noise from a binarized image of the set of binarized images based on at least one of a horizontal profile and a vertical profile of the binarized image;
detect one or more clusters of characters in the binarized image by a character detection unit based on at least one cluster constraint of the group comprising number of characters, size and orientation of characters, spacing between characters, aspect ratio and slope of characters; and
recognize a set of characters from the detected one or more clusters of characters by a character recognition unit, wherein a character of the set of characters is associated with a confidence value.
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Abstract
The present invention discloses methods, systems and computer programmable products for detecting license plates and recognizing characters in the licence plates. The system receives an image and identifies one or more regions including a license plate. The one or more regions are converted into a plurality of binarized images, which are then filtered to remove noise. Next, one or more clusters of characters are identified in the plurality of binarized images. The one or more clusters of characters are analyzed to recognize a set of characters, wherein each character in the set includes a confidence value.
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Citations
20 Claims
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1. A license plate detection and recognition (LPDR) system comprising of:
a processor, a non-transitory storage element coupled to the processor, encoded instructions stored in the non-transitory storage element, wherein the encoded instructions when implemented by the processor, configure the LPDR system to; receive an image by an image input unit, wherein the image input unit receives the image from at least one of an image capturing device, a network, a computer and a memory unit; detect one or more regions in the image by a license plate detection unit, wherein a region of the one or more regions includes a license plate, the license plate detection unit further comprising; a binarization unit configured to generate a set of binarized images of the region using at least one of a multi-scale difference of Gaussian filter and a variable adaptive threshold (T), wherein the variable adaptive threshold (T) is computed based on at least one parameter of a set of parameters computed locally in a window centered at a location in the region; and a filtration unit configured to remove noise from a binarized image of the set of binarized images based on at least one of a horizontal profile and a vertical profile of the binarized image; detect one or more clusters of characters in the binarized image by a character detection unit based on at least one cluster constraint of the group comprising number of characters, size and orientation of characters, spacing between characters, aspect ratio and slope of characters; and recognize a set of characters from the detected one or more clusters of characters by a character recognition unit, wherein a character of the set of characters is associated with a confidence value. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A computer programmable product for detecting a region containing a license plate and, detecting and recognizing a set of characters in the region, the computer programmable product being a part of a license plate detection and recognition (LPDR) system, the computer programmable product including a set of instructions, that are when executed by a processor of the LPDR system, causes the LPDR system to:
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receive an image, wherein the image is received from at least one of an image capturing device, a network, a computer and a memory unit; detect one or more regions in the image, wherein a region of the one or more regions includes a license plate, further comprising; generate a set of binarized images of the region using at least one of a multi-scale difference of Gaussian filter and a variable adaptive threshold (T), wherein the variable adaptive threshold (T) is computed based on at least one parameter of a set of parameters computed locally in a window centered at a location in the region; and remove noise from a binarized image of the set of binarized images based on at least one of a horizontal profile and a vertical profile of the binarized image; detect one or more clusters of characters in the binarized image based on at least a cluster constraint of the group comprising number of characters, size and orientation of characters, spacing between characters and slope of characters; and recognize a set of characters from the detected one or more clusters of characters, wherein a character of the set of characters is associated with a confidence value. - View Dependent Claims (12, 13, 14, 15, 16)
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17. A method for detecting and recognizing a license plate, the method comprising:
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detecting one or more regions in an image, wherein a region of the one or more regions includes a license plate, comprising; generating a set of binarized images of the region using at least one of a multi-scale difference of Gaussian filter and a variable adaptive threshold (T), wherein the variable adaptive threshold (T) is computed based on at least one parameter of a set of parameters computed locally in a window centered at a location in the region; and removing noise from a binarized image of the set of binarized images based on at least one of a horizontal profile and a vertical profile of the binarized image; detecting one or more clusters of characters in the binarized image based on at least one cluster constraint of the group comprising number of characters, size and orientation of characters, spacing between characters and slope of characters; and recognizing a set of characters from the detected one or more clusters of characters, wherein a character of the set of characters is associated with a confidence value. - View Dependent Claims (18, 19, 20)
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Specification