Aspose optical mark recognition API upgrade project

New consulting request

In August 2022, we received a consulting request from a customer who was developing an OMR ballot project for U.S. elections and was utilizing our Aspose.OMR for .NET API in the background. While our API was found to be useful, the customer had a list of new features that they wanted to be implemented into our API through the consulting project, and he also explained everything through the sample ballot file that he provided. One of the features was adding the fifth reference point to the ballot so that orientation could be determined because at that moment our API was not recognized ballot that was orientated upside down.

Aspose.OMR for .NET API

Aspose.OMR for .NET is a reliable and versatile programming API for designing and automatically recognizing hand-filled answer sheets, surveys, tests, ballots, SAT exam forms, insurance claims, and similar documents in which respondents answer a question by drawing a random mark in a circle or square.

Working on the project

We found that all the requests were acceptable and benefitial for our Aspose.OMR for .NET API, so we accepted the consulting request and started working on the project.

In Aspose we have a team that is in charge of Aspose.OMR for .NET API and they were actually working on the API, however, consulting team was communicating between customer and developer, analyzing all the feedback and requests, testing solutions, and attending the meetings. In essence, the customer was communicating with only one person, but in the background, we worked as a team.

The customer was kept informed of the progress once a week, and at the end of each month, we published a new release of the Aspose.OMR .NET API that included all the features that were completed. The customer’s feedback was precise and useful, which helped the project go smoothly.

Finishing the project

After two months of consulting, the project was completed, and the customer was pleased with the outcome. This type of project is highly appreciated by our team as it not only benefits the customer, but also helps improve our API.