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Jurizza Cuaresma 

 
BSc [Hons] Creative Computing

I'm an aspiring full-stack developer, passionate about typography, web accessibility, and UI/UX design.

The landing page of my web app.
The Cloud Vision API offers text detection features that use Optical Character Recognition (OCR) to identify typed, scanned or handwritten text in an image or document. The image shows text extracted from a PDF document.
Typesetting properties such as Typeface, size, leading, and kerning can be determined by the user for a more personalised reading experience.
A video demonstrating customisation options of a PDF that was uploaded to the web app.
Responsive typesetting using modern CSS principles.
Users can write content, take a photo and upload to Clear where the content will be output as a PDF.
Hierarchy and contrast can be achieved using a unique writing system. Each piece of the text is preceded by a symbol. A letter is combined with square brackets to denote a heading [H], subheading [S], and paragraph [P]. When detected, these symbols will be output as different-sized headings, giving nuance and hierarchy to digitised content.
The resulting output from the two images above.
Uploading an image that has handwritten text in it
Project Description

The aim of this project was to build a research-based web application designed to improve the reading experience of typed, scanned, or handwritten text in documents in Portable Document Format (PDF) for a diverse range of users. The application was developed using the MERN stack and integrated with other packages and libraries such as Google Cloud Storage and Google Cloud Vision API. Modern CSS practices and accessibility were also considered throughout the development. Users can customise typesetting–facilitating a more individual reading experience.


The Application of Inclusive Design and Optical Character Recognition (OCR) to Enhance the On-Screen Reading Experience

In a report published by the Nielsen Norman Group, usability and readability problems are encountered by users when they read PDFs on screen (2020). A number of studies have also shown that the navigation of PDFs causes slow task completion and poor user experience. The majority of the 1,224 screen reader users who participated in the survey carried out by WebAIM (2018) believe that PDFs are likely to cause accessibility issues.

The research conducted for this project compares the experiences of reading in print with reading on-screen and investigates the effects of each reading medium on learning. While many studies indicate that many still prefer reading printed text and on-screen text are not always suitable for intensive reading and better retention of information, results show that there is no significant difference between reading media in relation to learning.

Additionally, the thesis explores the importance of web accessibility in developing functional and accessible user interfaces. It looks into solutions to improve the on-screen reading experience and to reduce the difficulties that users with disabilities can have when accessing information presented on the web. The solutions that are highlighted in the thesis are Inclusive Design techniques.

Lastly, the thesis discusses how OCR works; how it is used in the application to identify text in PDFs and images and to transform handwritten text into discernible text; and how it is combined with JavaScript, HTML, and CSS to display the extracted text on a web page.

Creative Computing
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