Barcode-reading system utilizing a machine learning model that is trained to predict decodability of an image by a barcode-decoding module

A system, comprising:

• a barcode-decoding engine that comprises a barcode-decoding module;
• an image data repository comprising a plurality of images processed by the barcode-decoding module and a plurality of decodability labels corresponding to the plurality of images, wherein a decodability label corresponding to an image indicates decodability of the image by the barcode-decoding module;
• a training engine that is executable by at least one processor to train a decodability machine learning model (MLM), using the plurality of images and the plurality of decodability labels, to predict decodability of a new image by the barcode-decoding module;
• and
• a deployment engine that is executable by the at least one processor to deploy the decodability MLM in a pre-decoding filter module in the barcode-decoding engine.

A barcode-reading device, comprising:

• a camera that is configured to capture images;
• a processor;
• memory that is communicatively coupled to the processor;
• and
• a barcode-decoding engine stored in the memory, the barcode-decoding engine comprising:
• a barcode-decoding module;
• a pre-decoding filter module comprising a decodability machine learning model (MLM) that is configured to predict decodability of an image by the barcode-decoding module;
• and
• a main module that is executable by the processor to provide an image captured by the camera to the pre-decoding filter module, receive a decoding prediction for the image from the pre-decoding filter module, and provide the image to the barcode-decoding module only if the decoding prediction indicates that the image is likely to be decodable by the barcode-decoding module.