As the Internet and World Wide Web have grown, many good things have come. If you have access to a computer, you can find a lot of information quickly and easily. Electronic devices can store and retrieve vast amounts of data in seconds. You no longer have to leave your house to get products and services you could only get in person. Documents can be changed from English to Urdu or from text to speech almost instantly, making it easy for people from different cultures and with different abilities to talk to each other. As technology improves, web developers and website visitors want more animation, colour, and technology. As computers get faster at processing images and other graphics, web developers use them more and more. Users who can see colour, pictures, animation, and images can help understand and read the Web and improve the Web experience. People who have trouble reading or whose first language is not used on the website can also benefit from using pictures.
But not all images help people understand and read the text they go with. For example, images just for decoration or picked by the people who made the website should not be used. Also, different factors could affect how easy it is to read graphical content, such as a low image resolution, a bad aspect ratio, a bad colour combination in the image itself, a small font size, etc., and the WCAG gave different rules for each of these problems. The rules suggest using alternative text, the right combination of colours, low contrast, and a higher resolution. But one of the biggest problems is that images that don't go with the text on a web page can make it hard to read the text. On the other hand, relevant pictures could make the page easier to read.
A method has been suggested to figure out how relevant the images on websites are from the point of view of web readability. This method combines different ways to get information from images by using Cloud Vision API and Optical Character Recognition (OCR), and reading text from websites to find relevancy between them. Techniques for preprocessing data have been used on the information that has been extracted. Natural Language Processing (NLP) technique has been used to determine what images and text on a web page have to do with each other. This tool looks at fifty educational websites' pictures and assesses their relevance. Results show that images that have nothing to do with the page's content and images that aren't very good cause lower relevancy scores. A user study was done to evaluate the hypothesis that the relevant images could enhance web readability based on two evaluations: the evaluation of the 1024 end users of the page and the heuristic evaluation, which was done by 32 experts in accessibility. The user study was done with questions about what the user knows, how they feel, and what they can do. The results back up the idea that images that are relevant to the page make it easier to read. This method will help web designers make pages easier to read by looking at only the essential parts of a page and not relying on their judgment.Programa de Doctorado en Ciencia y Tecnología Informática por la Universidad Carlos III de MadridPresidente: José Luis Lépez Cuadrado.- Secretario: Divakar Yadav.- Vocal: Arti Jai
