Design And Implementation Of Papers Review System On Mobile Terminal Basedon Android

Examination, as a way to measure teaching quality, has been adopted by education. Among them, the review work of the written examination process is both time-consuming and error-prone in the exam. Computer technology has brought light for the realization of automatic marking system and it has been widely used in large-scale review paper work.In recent years, with the vigorous development of the mobile Internet, smart phones and touch smart devices quickly appear in people’s lives. With more and more powerful hardware configuration,people’s life has become more comfortable and the way how people work has become more convenient.Android system appears under the high speed development of mobile Internet. According to statistics, since2010, the Android system has gradually become the world’s most widely used operating system of mobile phone. So research and development in this essay is based on Android and to design a automatic marking software based on Android for teachers is a meaningful work. At present, our country’s traditional exam answer sheet of objective topic part mainly exists in the form.To this answer sheet, the article combines the mobile phone of Android with image library of OpenCV. On the mobile terminal, a kind of automatic marking scheme is designed which is simple and easy to use, and a mobile marking system is developed on the answer sheet. The system includes modules of image acquisition, image preprocessing, tilt correction, image forms, form image orientation and character recognition. The experimental results show that the automatic marking scheme has the advantages of high efficiency and it’s simple and easy to use. This system is suitable to promote.The automatic marking system is completed designedbased on Android,and the research shows progress in three aspects. Firstly, the traditional method of projection profile is improved and the improved algorithm is verified by experiment that it has better efficiency. Secondly, to form image positioning and image resolution module, thealgorithm is optimized and make up for positioninginaccuracy of the traditional form localization algorithm in special situation. Thirdly, for handwritten character recognition module, this essay improves the thirteen feature extraction method which is applicable to handset.