Deep learning analytics


Typographic image detection using deep learning technique
brings down operational cost.

IndustryTechnology Product

Year2012 – Ongoing

RoleDeep Learning, DCNN

TechnologyDCNN, OpenCV, Python Keras, Tesseract, OCR Engine

Fontli, a Social network for typoholics

Fontli is a typography community platform that identifies images without typographic content and marks them as spam. The requirement was to introduce a moderation process to sift out non-typographic images (such as selfies and scenery) that are irrelevant to the typographic community.

Deep learning algorithms help spot the typeface

We employed the Deep Convolutional Neural Network (DCNN) technique to classify typographic/ non-typographic images and OpenCV to get rid of selfies and group photos. Tesseract was used for detecting text within an image and Python Keras library (we used over 45,000 images), to train the network.


Neural network see the letters

Fontli could achieve 90% accuracy based on historical data—the accuracy will improve with time. There was also an overall reduction in operational cost by replacing manual validation with technology.