DECODING BARCODES FROM IMAGES WITH VARYING DEGREES OF FOCUS

Various algorithms are presented that enable an image of a barcode, captured by a camera of an electronic device, to be analyzed and decoded for use in obtaining information about an object or item associated with the barcode. The algorithms can account for variations in focus of the image, as may result in blur due to movement or a lack of auto-focus features. An offline training phase can be used to generate a set of possible symbol appearance templates, where at least some of the templates reflect simulations for varying levels and types of noise in an image. A decoding phase compares these templates to a captured image and performs a sequence-wide optimization to determine the overall most likely sequence of digits.