  Detecting and extracting information from Machine-Readable Zone (MRZ) on
passports and visas is becoming increasingly important for verifying document
authenticity. However, computer vision methods for performing similar tasks,
such as optical character recognition (OCR), fail to extract the MRZ given
digital images of passports with reasonable accuracy. We present a specially
designed model based on convolutional neural networks that is able to
successfully extract MRZ information from digital images of passports of
arbitrary orientation and size. Our model achieved 100% MRZ detection rate and
98.36% character recognition macro-f1 score on a passport and visa dataset.
