Font Attributes for Font Recognition and Similarity

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 recognize a font in rendered text in an image or determine similarity of the font in the rendered text in the image to other fonts, 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 based at least in part on training data that includes one or more relative attributes that describe relations of characteristics of fonts, one to another; using the model, by the one or more computing devices, to:
recognize the font used for the rendered text in the image; ordetermine similarity of the font used for the rendered text in the image with respect to one or more of a plurality of fonts; and controlling output of a result of the recognized font or the determined similarity in a user interface by the one or more computing devices.