Android-Based Text Recognition on Receipt Bill for Tax Sampling System
Rahmat, Romi Fadillah
Nababan, Erna Budhiarti
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Text is an element which provides information to the readers. However, not all text is informative, some are still in need to be processed to generate information. In text processing process, data is required to be inputted into the system. The input process will be easier if the text is already in digital form. The main issue is when the text is in the non-digital form such as in the form of image. This image should be converted into a form which recognized by the machine. Therefore, an approach is required to be able to identify the text on the images, in expectation to generate text that can be processed by the machine. The method proposed for this research to identify the text is Convolutional Neural Network. Before and after entering the identification process, the input image will go through several pre-processing and post-processing phases to select which text to be displayed as a result. The testing process used images of receipt taken at the distance of 10cm and 12 cm. The result showed the accuracy rates of the testing using images of receipt taken at the distance of 10cm and 12 cm are 95% and 85% respectively.