Peningkatan Akurasi Pembacaan Lembar Jawaban Komputer dengan Memperbaiki Ketidaksimetrisan Citra Hasil Pemindaian Menggunakan Transformasi Homografi
 Prayitno Prayitno (Universitas Dian Nuswantoro, Semarang, Indonesia)
Guruh Fajar Shidiq (Universitas Dian Nuswantoro, Semarang, Indonesia)
Ahmad Zainal Fanani (Universitas Dian Nuswantoro, Semarang, Indonesia)
(*)M. Arief Soeleman  (Universitas Dian Nuswantoro, Semarang, Indonesia)
(*) Corresponding Author Submitted: August 12, 2023; Published: October 22, 2023 |
Abstract
Answer Sheet Reading Computers are one of the technologies for converting images into information which continues to develop until now. Some of the applications of this technology include correcting various school exams, psychological tests, surveys and voting. Accuracy is something that is often a problem in various studies on reading computer answer sheets. Accuracy is greatly influenced by the scanned image. In the process of scanning computer answer sheets, images often produce asymmetry, such as tilting, shifting and dilatation.The process of scanning computer answer sheets often produces asymmetrical images, such as tilted, shifted and dilated. This incident will affect the accuracy of the results of reading the computer answer sheet, due to deformation of the shape between the reference image and the scanned image. This study aims to improve asymmetric images to become symmetrical with the Homografi transformation in order to get better reading accuracy. The results showed that the improvement of image symmetry with Homografi transformation was better than the skew correction method. This is shown from the respective RMSE values, the Homografi transformation method produces an RMSE value of 51.54 and the skew correction method produces a value of 67.04. The results of the study also stated that the accuracy of reading computer answer sheets with the Homografi transformation method was better than skew correction. The skew correction accuracy is 95.8%, while the Homografi transformation is 99.3%.
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