**1. Introduction**

According to the World Health Organization, at least 2.2 billion people have a visual impairment, and the number is likely to increase with population growth and aging [1]. For them, understanding visual information is one of the main challenges.

To improve the accessibility of images for people who are blind or have low vision (BLV), a number of studies have been conducted to assess the effectiveness of custommade tactile versions of images [2–8]. Cavazos et al. [5], for instance, proposed a 2.5D tactile representation of the artwork where blind users can feel the artwork by touch while listening to audio feedback. Holloway et al. [7] also investigated tactile graphics and 3D models to deliver map information such as the number of entrances, location and direction of certain landmarks. This approach with extra tactile feedback is found to be effective as it can deepen one's spatial understanding of images by touch [9–11]. However, it requires additional equipment, which potential users have limited access to (e.g., 3D printer, custom devices). Moreover, tactile representations need to be designed and built for each image, and thus it is not ideal for supporting a number of different images in terms of time and cost.

Meanwhile, others have relied on digital devices that are commercially available (e.g., PC, tablets, smartphones) for conveying image descriptions (also known as alternative text or alt text) on the web in particular [12–14]. For instance, Zhong et al. [13] generated alt text for images on the web that are identified as important using crowdsourcing. In addition, Stangl et al. [12] used natural language processing and computer vision techniques to automatically extract visual descriptions (alt text) on online shopping websites for clothes. Unlike tactile approaches, this software-based approach is more scalable, especially with the help of crowds or advanced machine learning techniques. However, listening to a set of

Image Accessibility for Screen Reader Users: A Systematic Review and a Road Map. *Electronics* **2021**, *10*, 953. https://doi.org/10.3390/ electronics10080953

Academic Editor: Juan M. Corchado

Received: 8 March 2021 Accepted: 5 April 2021 Published: 16 April 2021

**Citation:** Oh, U.; Joh, H.; Lee, Y.

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

verbal descriptions of an image may not be sufficient for understanding its spatial layout of content or objects within each image.

To leverage the issues of two different approaches above, researchers have worked on touchscreen-based image accessibility that enables users to explore different regions on images by touch to help them have a better spatial understanding. In this paper, to gain a more holistic perspective of this approach by examining the current states and identifying the challenges to be solved, we conducted a systematic literature review of 33 papers, following PRISMA guidelines [15]. To be specific, our goal is to identify the following: supported image types, provided information, collection and the delivery method of the information, and the involvement of screen reader users during the design and development process.

As a result, we found that research studies on touchscreen-based image accessibility have been mostly focused on maps (e.g., directions, distance), graphs (e.g., graph type, values) and geometric shapes (e.g., shape, size, length) using audio and haptic feedback. Moreover, it revealed that the majority of them manually generated image-related information or assumed that the information was given. We also confirmed that while most user studies are conducted with participants who are blind or have low vision for user evaluation, a few studies involved target users during the design process.

In addition, to demonstrate how other types of images can be made accessible using touchscreen devices, we introduce two of our systems: AccessArt [16–18] for artwork and AccessComics [19] for digital comics.

Based on the challenges and limitations identified by conducting systematic review and from our own experience of improving image accessibility for screen reader users, we sugges<sup>t</sup> a road map for future studies in this field of research. The following are the the contributions of our work:


The rest of the content covers a summary of prior studies on image accessibility and touchscreen accessibility for BLV people (Section 2), followed by a description of how we conducted a systematic review (Section 3), and the results (Section 4), demonstrations of two systems for improving the accessibility of artwork and digital comics (Section 5), discussions on the current limitations and potentials of existing work and suggestions on future work (Section 6), and conclusions (Section 7).

### **2. Related Work**

Our work is inspired by prior work on image accessibility and touchscreen accessibility for people who are blind or who have low vision.
