System and Method for Symbol Detection
AssigneeDatalogic USA, Inc.
InventorsStefano SANTI, Thomas PRIHODA
Life of this patent
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Abstract
An optical symbol detector has an input operative to receive a captured image frame. The detector includes a feature extractor engine coupled to the input to produce a downscaled descriptor map based on the captured image frame, the descriptor map including a convolutional map of blocks of the captured image frame. The detector further includes a coarse estimator engine coupled to an output of the feature extractor engine to produce a detection indication and localization information of an optical pattern indicative of a machine-readable symbol based on the downscaled descriptor map.
Claims20
An optical symbol detector, comprising:
- an input operative to receive a captured image frame;
- a feature extractor engine coupled to the input to produce a downscaled descriptor map based on the captured image frame, the downscaled descriptor map including a convolutional map of blocks of the captured image frame;
- and
- a coarse estimator engine coupled to an output of the feature extractor engine to produce a detection indication and localization information of an optical pattern indicative of a machine-readable symbol based on the downscaled descriptor map, wherein the coarse estimator engine includes a trained decision tree cascaded with a trained neural network.
(canceled)
A method for operating an optical symbol detector, comprising:
- receiving a captured image frame;
- autonomously computationally producing a downscaled descriptor map based on the captured image frame, the downscaled descriptor map including a convolutional map of blocks of the captured image frame;
- and
- autonomously computationally producing a detection indication and localization information of an optical pattern indicative of a machine-readable symbol based on the downscaled descriptor map;
- wherein producing the downscaled descriptor map includes:
- partitioning the image frame into blocks;
- and
- for each block:
- computing a downscaled descriptor based on an S-transform operation to produce a vector representative of that block;
- and
- computing a convolutional descriptor based on the vector of the block convolved with a kernel that includes vectors of neighboring blocks;
- wherein the downscaled descriptor map comprises a set of convolutional descriptors of the blocks.
Dependencies are inferred from the claim text.