  Fonts are one of the most basic and core design concepts. Numerous use cases
can benefit from an in depth understanding of Fonts such as Text Customization
which can change text in an image while maintaining the Font attributes like
style, color, size. Currently, Text recognition solutions can group recognized
text based on line breaks or paragraph breaks, if the Font attributes are known
multiple text blocks can be combined based on context in a meaningful manner.
In this paper, we propose two engines: Font Detection Engine, which identifies
the font style, color and size attributes of text in an image and a Font
Prediction Engine, which predicts similar fonts for a query font. Major
contributions of this paper are three-fold: First, we developed a novel CNN
architecture for identifying font style of text in images. Second, we designed
a novel algorithm for predicting similar fonts for a given query font. Third,
we have optimized and deployed the entire engine On-Device which ensures
privacy and improves latency in real time applications such as instant
messaging. We achieve a worst case On-Device inference time of 30ms and a model
size of 4.5MB for both the engines.
