Date of Award:

5-2016

Document Type:

Dissertation

Degree Name:

Doctor of Philosophy (PhD)

Department:

Computer Science

Committee Chair(s)

Vladimir Kulyukin

Committee

Vladimir Kulyukin

Committee

Nicholas Flann

Committee

Xiaojun Qi

Committee

Haitao Wang

Committee

David Paper

Abstract

Vision-based extraction of nutritional information from nutrition labels (NLs) available on most product packages is critical to proactive nutrition management, because it improves the user’s ability to engage in continuous nutritional data collection and analysis. However, even users who are health conscious find it difficult to keep track of their nutrition intake due to lack of time, motivation, or training. In order to make nutrition management more proactive we present a Proactive NUTrition Management System (PNUTS), which aims to make nutrition management more user friendly and proactive using computer vision techniques running on smartphones which are ubiquitous and powerful computers at the same time. There are essentially two modules in PNUTS. First of all, a skewed barcode scanning module capable of reading barcodes irrespective of the camera alignment and a second module which can detect the skew angle of text in nutrition labels and eventually read the text using optical character recognition.

Checksum

a9ab3e3969ec782dbbbc2c6d7db1f179

Download

Share

COinS

Copyright for this work is retained by the student. If you have any questions regarding the inclusion of this work in the Digital Commons, please email us at .