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Contribution Details
| Type | Bachelor's Thesis |
| Scope | Discipline-based scholarship |
| Title | TextDigitizer: design and implementation of a text recognition application on the iPhone platform |
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| Institution | University of Zurich |
| Faculty | Faculty of Economics, Business Administration and Information Technology |
| Number of Pages | 79 |
| Date | 2011 |
| Abstract Text | In this thesis we present our prototype for the iPhone operating system. It recognizes text on an image and shows articles related to the text. In case the user wants to limit the text to a particular area, they can crop the image. We integrated two existing optical character recognition libraries (Tesseract and GOCR) to recognize the text. The libraries are open-source and work off-line on the device itself. To enhance the recognition rate we preprocess the image and postprocess the recognized text. Based on our prototype we conducted usability tests with surveys (interviews and online questionnaires). An evaluation with test images proved the effectiveness and accuracy of the optical character libraries. The conclusions from those evaluations helped us to implement a prototype that recognizes text fast and with high accuracy. |
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