CPC G06V 20/625 (2022.01) [G06V 10/774 (2022.01); G06V 20/54 (2022.01); G06V 30/148 (2022.01)] | 17 Claims |
1. A method comprising:
analyzing a plurality of frames of a video of an object to detect a license plate associated with the object;
upon detecting the license plate in a frame of the plurality of frames, determining a subset of frames containing the license plate by analyzing neighboring frames associated with the frame to detect the license plate;
determining a plurality of characters in the license plate by, for each character in the plurality of characters:
based on a location of the character in the plurality of characters, determining corresponding characters in each frame in the subset of frames; and
determining, to be a part of the plurality of characters, a most frequent character among the character and the corresponding characters;
obtaining a plurality of bounding boxes indicating locations of the plurality of characters the locations represented by Cartesian coordinates;
obtaining a plurality of nodes based on the plurality of bounding boxes, wherein a respective location of each respective node indicates a respective location of a respective box in the plurality of bounding boxes;
determining a distance based on a first location of a first node of the plurality of nodes and a second location of a second node of the plurality of nodes;
determining whether the distance is below a threshold, wherein the threshold is computed based on a length of a long side of a box of the plurality of bounding boxes;
based on a determination that the distance is below the threshold, creating a first edge between the first and second nodes, thereby obtaining a first graph including the first node, the second node, and the first edge;
determining a leftmost node in the first graph based on first Cartesian coordinates representing the first location and second Cartesian coordinates representing the second location; and
ordering the plurality of characters into a sequence of characters based on the first graph and the leftmost node in the first graph.
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