This article describes JECT-OMR, a system that analyzes digital images representing scans of multiple-choice tests compiled by students. The system performs a structural analysis of the document in order to get the chosen answer for each question, and it also contains a bar-code decoder, used for the identification of additional information encoded in the document. JECT-OMR was implemented using the Python programming language, and leverages the power of the Gamera framework in order to accomplish its task. The system exhibits an accuracy of over 99% in the recognition of marked and non-marked squares representing answers, thus making it suitable for real world applications
@article{arxiv.1105.3834,
title = {A Multiple-Choice Test Recognition System based on the Gamera Framework},
author = {Andrea Spadaccini and Vanni Rizzo},
journal= {arXiv preprint arXiv:1105.3834},
year = {2011}
}