Analyzing font similarity for presentation
AssigneeMonotype Imaging Inc.
InventorsSampo Juhani Kaasila, Anand Vijay, Jitendra Kumar Bansal
Life of this patent
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Abstract
A system includes a computing device that includes a memory configured to store instructions. The system also includes a processor to execute the instructions to perform operations that include receiving data representing features of a first font and data representing features of a second font. The first font and the second font are capable of representing one or more glyphs. Operations also include receiving survey-based data representing the similarity between the first and second fonts, and, training a machine learning system using the features of the first font, the features of the second font and the survey-based data that represents the similarity between the first and second fonts.
Claims36
A computing device implemented method comprising:
- receiving data representing a pair of fonts, wherein each font of the pair of fonts is capable of representing one or more glyphs;
- determining a level a similarity for the pair of fonts using a machine learning system, the machine learning system being trained using a difference between features of a first font and features of a second font, and using data representing similarity between the first and second fonts as determined by one or more individuals;
- and
- producing a list of fonts for presentation based on the level of similarity for the font pair, wherein a presented order of fonts in the produced list is based upon a level of similarity between a focus font and other fonts.
A system comprising:
- a computing device comprising:
- a memory configured to store instructions;
- and
- a processor to execute the instructions to perform operations comprising:
- receiving data representing a pair of fonts, wherein each font of the pair of fonts is capable of representing one or more glyphs;
- determining a level a similarity for a pair of fonts using a machine learning system, the machine learning system being trained using features of a first font and features of a second font, and using data representing similarity between the first and second fonts as determined by one or more individuals;
- and
- producing a list of fonts for presentation based on the level of similarity for the font pair, wherein a presented order of fonts in the produced list is based upon a level of similarity between a focus font and other fonts.
One or more non-transitory computer readable media storing instructions that are executable by a processing device, and upon such execution cause the processing device to perform operations comprising:
- receiving data representing a pair of fonts, wherein each font of the pair of fonts is capable of representing one or more glyphs;
- determining a level a similarity for a pair of fonts using a machine learning system, the machine learning system being trained using a difference between features of a first font and features of a second font, and using data representing similarity between the first and second fonts as determined by one or more individuals;
- and
- producing a list of fonts for presentation based on the level of similarity for the font pair, wherein a presented order of fonts in the produced list is based upon a level of similarity between a focus font and other fonts.
Dependencies are inferred from the claim text.