Image processing methods that take place in different areas of life from identification to traffic flow control are starting to be used on mobile devices. Hence, usage of optical mark recognition systems (OMRS) on mobile devices is also not widespread as it is for image processing applications. A mobile OMRS is developed using image processing methods. In this developed system, image enhancement, edge detection, and tilt-shifting operations were performed on the optical answer paper images that are obtained using mobile devices. Within the scope of this study, it is aimed to achieve the maximum success of image processing operations on a mobile device that has limited hardware resources. The evaluation of optical answer papers that are obtained using mobile devices is performed using the image processing methods and algorithms developed within the scope of this study. The developed system is tested using different type of optical answer papers. According to the test results, the developed system provides a flexible and efficient use and partly eliminates previous work constraints. The success rate of the developed system is determined to be 93.54% using the test results obtained.
KEYWORDS: Edge detection, Detection and tracking algorithms, Image processing, Cameras, Scanners, Image resolution, Image filtering, Convolution, Human-computer interaction, Global system for mobile communications
Optical Mark Recognition (OMR) is a traditional data input technique and an important human computer interaction technique which is widely used in education testing. This paper proposes a new idea for grading multiple-choice test which is based on a camera on smartphone. The system key techniques and relevant implementations, which include the image scan, edge detection and reduction of brightness on colorful bubble form images, are presented.
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