| Summary: | 碩士 === 長榮大學 === 職業安全與衛生學系碩士班 === 100 === For many scholars in the areas of safety and health, it is very important to collect the quantitative information through questionnaire surveys. In a large-scale survey, hoping that the data of the questionnaire analysis can be more accurate and representative, researchers collect and manage a huge amount of questionnaires, which makes the data input become one of the most important steps in the analytical process. Data input of questionnaires can be done manually or through the card reading devices for further analysis in computers. For manual input people need to consider the questionnaire layouts and the labor cost, while using the card reading devices requires much higher cost since those devices are rental and the questionnaires are made of some specified materials. This research are, therefore, to develop by machine vision an automatic input system, which let researchers be able to conduct a large amount of questionnaire input without the limitations of the layout designs and paper materials.
The questionnaire input system developed in this thesis integrates a number of hardware and software modules. When the system is in operation, each questionnaire sent by a paper feeder is captured by a camera in real time, and analyzed in the graphical user interface. The data acquired after image processing are then saved as a text file. Several experiments were conducted to assess the accuracy and the efficiency of the system. In the performance experiment, we processed a plenty of questionnaires answered using various pens with the specified colors, as well as some specified marks. It was found by statistical analyses that there was no significant difference in the accuracies of all colors; and accuracies answered with checks, ticks and crosses were significantly better than those answered with circles. Of all the accuracies of the software to recognize the checkboxes filled with checks in various colors ranged from 98.77%~99.17%; and to recognize other checkboxes answered with different marks were around 95.32%~99.21%. In the last experiment, we identified that the average processing time for a blank questionnaire was 3119.78ms, and for an answered one was 3154.85ms, which means that the developed software is capable of processing a questionnaire during 3.2 seconds. It is concluded that this automatic questionnaire input system is indeed able to increase the accuracy and efficiency in questionnaire surveys.
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