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Аннотация.
В статье рассматривается задача локализации паспорта гражданина Российской Федерации на фотографиях, где документ занимает небольшую часть кадра. Проблема особенно актуальна для систем удаленной верификации, требующих от пользователя загрузки селфи с паспортом. Малый масштаб затрудняет распознавание и локализацию документа ввиду меньшего разрешения. Для повышения точности локализации предлагается сверхлегкая нейросетевая модель YOLOPassport для локализации области паспорта, сводя задачу к случаю фиксированного масштаба документа. По сравнению с компактными детекторами YOLO, YOLO-Passport имеет на порядок меньше операций и параметров. Предложенный подход позволил повысить полноту детекции паспорта РФ с 91.6% до 97.4%. Время работы модели на CPU составляет 3 мс, а ее размер в 8 битном формате всего 340 КБ, что делает ее эффективной для применения в промышленных системах и веб-приложениях на базе WASM.
Ключевые слова:
распознавание документов, глубокое обучение, детекция объектов, YOLO.
DOI 10.14357/20718632250301
EDN AEBPRY
Стр. 3-12.
Литература
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