What is it about?
The paper, therefore, researches ways to enhance existing digital image recognition technologies to benefit blind users by reviewing limitations and proposing a comprehensive usability checklist. The study reviews how existing technologies stand up in terms of dimensions like accuracy, adequacy, appropriateness, sufficiency, functionality, and ergonomic suitability of the information. It attempts to lay some sort of standards regarding digital product design for blind/visually impaired users and also ensures greater awareness and attitude toward visually disabled persons during the development of image recognition software.
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Why is it important?
The study is very critical and opportune because it responds to the increasing dependence of persons with visual impairments on digital tools for accessibility. It thus provides a much-needed framework through a review of limitations in image recognition technologies that are in existence while developing a usability checklist to raise the bar for the design and functionality of digital products. This study will directly have an impact on the lives of the blind and visually impaired; for instance, the tools they use are accurate, good enough, and ergonomically fitted for their needs. The study furthers awareness and attitude change among the developers for incorporation of inclusive practices in the development of image recognition software. It is potentially the benchmark for innovators in a period when accessibility is being refashioned by technological advancement. Ensuring this means inclusivity and a higher quality of life for visually impaired persons. Its practical implications for product designers and developers rebound as a serious contribution to accessibility advocacy and, more generally, to the field of assistive technology development.
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This page is a summary of: Image Recognition Tools for Blind and Visually Impaired Users: An Emphasis on the Design Considerations, ACM Transactions on Accessible Computing, October 2024, ACM (Association for Computing Machinery),
DOI: 10.1145/3702208.
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