公开(公告)号：US20180114097A1

公开(公告)日：2018-04-26

申请号：US15853120

申请日：2017-12-22

Applicant: Adobe Systems Incorporated

Inventor： Zhaowen Wang ,  Luoqi Liu ,  Hailin Jin

IPC: G06K9/62 ,  G06K9/66

CPC classification number: G06K9/6257 ,  G06K9/4628 ,  G06K9/6272 ,  G06K9/6277 ,  G06K9/66 ,  G06K9/6828 ,  G06K2209/01 ,  G06N3/0454

Abstract: 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.

公开(公告)号：US20180082156A1

公开(公告)日：2018-03-22

申请号：US15269492

申请日：2016-09-19

Applicant: Adobe Systems Incorporated

Inventor： Hailin Jin ,  Zhaowen Wang ,  Gavin Stuart Peter Miller

IPC: G06K9/68 ,  G06F17/21

CPC classification number: G06K9/6828 ,  G06F17/214

Abstract: Font replacement based on visual similarity is described. In one or more embodiments, a font descriptor includes multiple font features derived from a visual appearance of a font by a font visual similarity model. The font visual similarity model can be trained using a machine learning system that recognizes similarity between visual appearances of two different fonts. A source computing device embeds a font descriptor in a document, which is transmitted to a destination computing device. The destination compares the embedded font descriptor to font descriptors corresponding to local fonts. Based on distances between the embedded and the local font descriptors, at least one matching font descriptor is determined. The local font corresponding to the matching font descriptor is deemed similar to the original font. The destination computing device controls presentations of the document using the similar local font. Computation of font descriptors can be outsourced to a remote location.

公开(公告)号：US20150120760A1

公开(公告)日：2015-04-30

申请号：US14068238

申请日：2013-10-31

Applicant: Adobe Systems Incorporated

Inventor： Zhaowen Wang ,  Jianchao Yang ,  Zhe Lin ,  Jonathan Brandt

IPC: G06F17/30

CPC classification number: G06F17/30265 ,  G06K9/6263 ,  G06K2209/27

Abstract: A system is configured to annotate an image with tags. As configured, the system accesses an image and generates a set of vectors for the image. The set of vectors may be generated by mathematically transforming the image, such as by applying a mathematical transform to predetermined regions of the image. The system may then query a database of tagged images by submitting the set of vectors as search criteria to a search engine. The querying of the database may obtain a set of tagged images. Next, the system may rank the obtained set of tagged images according to similarity scores that quantify degrees of similarity between the image and each tagged image obtained. Tags from a top-ranked subset of the tagged images may be extracted by the system, which may then annotate the image with these extracted tags.

Abstract translation: 系统配置为使用标签注释图像。 如所配置的，系统访问图像并生成图像的一组向量。 可以通过数学变换图像来生成向量集合，例如通过对图像的预定区域应用数学变换。 然后，系统可以通过将搜索标准的向量集合提交给搜索引擎来查询标记图像的数据库。 数据库的查询可以获得一组标记的图像。 接下来，系统可以根据量化图像和所获得的每个标记图像之间的相似度的相似度分数来对获得的标记图像集进行排序。 来自标记图像的顶级子集的标签可以由系统提取，然后系统可以利用这些提取的标签来注释图像。