Vision CortexSymbolic BarcodeImage SimplificationImage VectorizationOptical Character RecognitionAbout UsSymCodeImpressionVTracer

Vision Cortex - Semantic Computer Vision

The goal of Semantic Computer Vision is to allow computers to understand the content of images and graphics as intended and perceived by humans, and construct a high level representation of such information.

This technology can be embodied in different applications:

Symbolic Barcode

We developed SymCode, a 2D barcode designed to be both human-readable and machine-readable.

Image Simplification

We developed Impression, a family of algorithms for image simplification and segmentation. It allows us to control the amount of visual information in an image in a quantitative manner.

Image Vectorization

We developed VTracer, a utility to convert raster images (like jpg & png) into vector graphics (svg). Our graphics pipeline is able to process high resolution scans and photographs and trace the content to output compact vector files.

Optical Character Recognition

We are developing a new Optical Character Recognition (OCR) engine from the ground up specifically for pictorial languages like Chinese, Korean and Japanese (CKJ) to encompass wider character sets and font variations.

About Us

The research group is led by alumnus Chris Tsang conjoining with several students and alumni from Hong Kong University of Science and Technology: Sanford Pun and Hill Tse .

We are actively looking for researchers and developers to engage in this R & D project. If you are interested in doing a FYP or thesis related to this topic, let's get in touch.

We promise to release the eventual outcome of this project as open source software and continue to develop it over the years to come.