Font Recognition using Text Localization

摘要

Font recognition and similarity determination techniques and systems are described. In a first example, localization techniques are described to train a model using machine learning (e.g., a convolutional neural network) using training images. The model is then used to localize text in a subsequently received image, and may do so automatically and without user intervention, e.g., without specifying any of the edges of a bounding box. In a second example, a deep neural network is directly learned as an embedding function of a model that is usable to determine font similarity. In a third example, techniques are described that leverage attributes described in metadata associated with fonts as part of font recognition and similarity determinations.

主权项

1. In a digital medium environment to improve image font recognition through use of text localization, a method implemented by one or more computing devices comprising:
obtaining a model, by the one or more computing devices, that is trained using machine learning as applied to a plurality of training images having text rendered using a corresponding font; predicting a bounding box, by the one or more computing devices, for text in an image received using the obtained model; and generating an indication of the predicted bounding box by the one or more computing devices, the indication usable to specify a region of the image that includes the text having a font to be recognized.