Machine learning technologies for assessing text legibility in electronic documents
AssigneeCimpress Schweiz GmbH
InventorVyacheslav Nykyforov
Life of this patent
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Abstract
Systems and methods for using machine learning to assess text legibility in an electronic document are disclosed. According to certain aspects, an electronic device may train a machine learning model using training data that includes at least a representation of a text legibility level in the training data. Additionally, the electronic device may input the electronic document into the machine learning model, which may analyze the electronic document and output a representation of the text legibility level of a set of textual content included in the electronic document. The electronic device may display the output for review and assessment by a user, who may use the electronic device to facilitate any modifications to the electronic document.
Claims14
A computer-implemented method of using machine learning to assess text legibility in an electronic document, the computer-implemented method comprising:
- training, by a computer processor, a machine learning model using a training set of electronic documents, each of the training set of electronic documents comprising (i) a training set of textual content, (ii) a training set of visual content, and (iii) a training representation of a text legibility level of the training set of textual content;
- storing the machine learning model in a memory;
- accessing, by the computer processor, input data comprising an electronic document that comprises a set of textual content and a set of visual content;
- analyzing, by the computer processor using the machine learning model, the input data;
- based on the analyzing, generating, by the machine learning model, a red-green-blue (RGB) representation of a text legibility level of the set of textual content of the electronic document, the RGB representation comprising (i) a first digital image depicting, as a first plane, a set of detected characters, (ii) a second digital image depicting, as a second plane, a set of legibility values corresponding to the set of detected characters, and (iii) a third digital image depicting, as a third plane, a set of text lines;
- generating, by the computer processor, a visual representation of the text legibility level of the set of textual content by combining the first plane, the second plane, and the third plane of the RBG representation;
- and
- displaying, via a user interface, the visual representation of the text legibility level of the set of textual content, wherein a color and a composition of the visual representation indicates the text legibility level of the set of textual content.
A system for using machine learning to assess text legibility in an electronic document, comprising:
- a memory storing a set of computer-readable instructions and data associated with a machine learning model;
- and
- a processor interfaced with the memory, and configured to execute the set of computer-readable instructions to cause the processor to:
- train a machine learning model using a training set of electronic documents, each of the training set of electronic documents comprising (i) a training set of textual content, (ii) a training set of visual content, and (iii) a training representation of a text legibility level of the training set of textual content,
- store the machine learning model in the memory,
- access input data comprising an electronic document that comprises a set of textual content and a set of visual content,
- analyze, using the machine learning model, the input data, and
- based on the analyzing, generate, by the machine learning model, a red-green-blue (RGB) representation of a text legibility level of the set of textual content of the electronic document, the RGB representation comprising (i) a first digital image depicting, as a first plane, a set of detected characters, (ii) a second digital image depicting, as a second plane, a set of legibility values corresponding to the set of detected characters, and (iii) a third digital image depicting, as a third plane, a set of text lines,
- generate a visual representation of the text legibility level by combining the first plane, the second plane, and the third plane of the RBG representation, and
- display, via a user interface, the visual representation of the text legibility level, wherein a color and a composition of the visual representation indicates the text legibility level of the set of textual content.
A non-transitory computer-readable storage medium configured to store instructions executable by a computer processor, the instructions comprising:
- instructions for training a machine learning model using a training set of electronic documents, each of the training set of electronic documents comprising (i) a training set of textual content, (ii) a training set of visual content, and (iii) a training representation of a text legibility level of the training set of textual content;
- instructions for storing the machine learning model in a memory;
- instructions for accessing input data comprising an electronic document that comprises a set of textual content and a set of visual content;
- instructions for analyzing, using the machine learning model, the input data;
- and
- instructions for, based on the analyzing, generating, by the machine learning model, a red-green-blue (RGB) representation of a text legibility level of the set of textual content of the electronic document, the RGB representation comprising (i) a first digital image depicting, as a first plane, a set of detected characters, (ii) a second digital image depicting, as a second plane, a set of legibility values corresponding to the set of detected characters, and (iii) a third digital image depicting, as a third plane, a set of text lines;
- instructions for generating a visual representation of the text legibility level by combining the first plane, the second plane, and the third plane of the RBG representation;
- and
- instructions for displaying, via a user interface, the visual representation of the text legibility level, wherein a color and a composition of the visual representation indicates the text legibility level of the set of textual content.
Dependencies are inferred from the claim text.