Regarding the tests carried out with lowercase letters, the application has found it more difficult to identify the text because the lowercase writing differs a lot between people and has too wide a variety of combinations. In this sense, we have carried out satisfactory writing tests on paper and on a white board, focusing the camera at 1 meter from it. In the tests of this functionality we have verified that it achieves greater precision with texts in capital letters with clear typography. Handwriting identification is a valuable feature that most text identification products and applications do not include.
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This identification is especially optimal in cases in which the texts present a great contrast with respect to the background color and, furthermore, this is as homogeneous as possible without presenting any drawing or figure.ĭuring the tests we have correctly identified texts from technical manuals with a white background and simple typography, as well as texts from advertising brochures with a white and red background and with more elaborate fonts. If the text has been correctly focused, the printed text identification has great precision. Good lighting is also recommended, for this, the application allows the activation of the flash from its own menu to illuminate texts in case the ambient lighting is reduced. It is very important to focus the text well, for this the application emits a series of voice prompts that indicate the orientation that the phone should have. The application has obtained good identifications with the printed texts, yes, always with the analysis functionality in the cloud active, since otherwise the identification is usually not of quality.
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To carry out our tests we are going to present a series of texts, both printed and handwritten, a QR code and images containing text downloaded from the internet. After its activation we quickly realize that as expected it is really optimized for use with screen readers and its functionalities are correctly labeled in Spanish. In this case we have activated the IOS Voiceover screen reader since it is the real way of interacting with the phone for a person with vision difficulties. Once the application is downloaded, we go through the different options to familiarize ourselves with it. In our case, we have tested the paid version of the application with its Cloud OCR feature that allows images to be sent to the cloud (internet) for a better text identification result. To carry out the tests we have used an Iphone 6S model terminal downloading the application from the Apple Store. We have tested the Prizmo Go application in different contexts together with our volunteer Andrés and in the following lines we summarize our impressions. Telephone for the elderly Doro Liberto 820 mini
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