We have tested the Prizmo Go application in different contexts together with our volunteer Andrés and in the following lines we summarize our impressions.
To carry out the tests we used an Iphone 6S model terminal downloading the Apple Store application. In our case we have tested the paid version of the application with its Cloud OCR feature that allows you to send the images to the cloud (internet) for a better text identification result.
Once the application is downloaded, we go through the different options to familiarize ourselves with it. In this case we have activated the IOS Voiceover screen reader since it is the real way to interact with the phone for a person with vision difficulties. 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.
For the realization of our tests we will present a series of texts both printed and handwritten, some QR code and images containing text downloaded from the internet.
The application has obtained good identifications with the printed texts, however, always with the functionality of analysis in the active cloud, since otherwise the identification is usually not of quality.
It is very important to focus the text well, for this the application issues a series of voice prompts that indicate the orientation that the telephone should have. It is recommended a good lighting, for this, the application allows the activation of the flash from its own menu to illuminate texts in case the ambient lighting is reduced.
If the text has been correctly focused, the identification of printed text has great precision. This identification is especially optimal in cases where the texts have a great contrast to the background color and this is also as homogeneous as possible without presenting any drawing or figure.
During the tests we have correctly identified texts of technical manuals with a blank background and simple typography, as well as texts of advertising leaflets with a white and red background and with more elaborate typographies.
Handwriting identification is a great value feature and that most text identification products and applications do not include.
In the tests of this functionality we have verified that it reaches a greater precision with texts in uppercase letters of clear typography. In this sense we have carried out satisfactory tests of writing on paper and on a whiteboard focusing the camera 1 meter away from it.
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 a variety of combinations too broad. In any case, some words that contained well-defined letters could be identified.
Regarding the identification of QR codes, during the tests we managed to identify some of the ones that we placed in front of the camera, but not in all cases we were able to access the link or link of them. For this functionality there are many more accurate free QR code reading applications.
Images that contain text
This functionality is designed to load images that contain text such as those that circulate through social networks and are impossible to read by a screen reader.
Your reading can be done by sending the image to Prizmo Go from your own WhatsApp or Facebook, or they can be loaded from a location on our phone where the image has been previously stored.
During the tests performed, the identification accuracy was low in the case of images that contained text mixed with figures and different elements and that showed poorly marked contrasts.
Prizmo Go is a simple, useful and usable application with numerous functionalities around the identification of texts. The application reaches an acceptable precision in its paid version since it is in this version that it sends texts to an internet server for processing and identification. The annual price is not high if you are going to make frequent use of it.
In any case, we miss a version of Android that allows its use to all those users with reduced or no vision using terminals of different ranges and brands.
During the tests, a high battery consumption was observed after making a continuous use of the battery. However, the data consumption is not high despite sending information to the cloud for identification and is an average of hundreds of KB for each image sent.
- Its simplicity and usability
- Handwriting identification not included in most OCRs
- The annual price is acceptable for the version with identification in the cloud, which is the one that allows a greater precision.
- It would be advisable to have an Android version
- The free version is not able to identify texts accurately
- The consumption of the battery is high if it is used continuously