MyUEVision: an application generating image caption for assisting visually impaired people

Purpose Visually impaired people usually struggle with doing daily tasks due to a lack of visual cues. For image captioning assistive applications, most applications require an Internet connection for the image captioning generation function to work properly. In this study, we developed MyUEVision, an application that assists visually impaired people by generating image captions that can work with and without the Internet. This work also involves reviewing some image captioning models for this application. Design/methodology/approach The author has selected and experimented with three image captioning models for online models and two image captioning models for offline models. The user experience (UX) design was designed based on the problems faced by visually impaired users when using mobile applications. The application is developed for the Android platform, and the offline model is integrated into the application for the image captioning generation function to work offline. Findings After conducting experiments for selecting online and offline models, ExpansionNet V2 is chosen for the online model and VGG16 + long short-term memory (LSTM) is chosen for the offline model. The application is then developed and assessed, and the results show that the application can generate image captions with or without the Internet, providing the best result when having an Internet connection, and the image is captured in good lighting with a few objects. Originality/value MyUEVision stands out for its both online and offline functionality. This approach ensures the image captioning generator works with or without the Internet, setting it apart as a unique solution to address the needs of visually impaired individuals.

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Publication Details

Journal
Journal of Enabling Technologies
Published
2024-09-02
DOI
https://doi.org/10.1108/jet-03-2024-0024
Citations
2
Primary Topic
Multimodal Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.50
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article

MyUEVision: an application generating image caption for assisting visually impaired people

Thai Huynh, Nha Tran, Hung Tan Nguyen, Toan Nguyen
2 citations
Journal of Enabling Technologies
Multimodal Machine Learning Applications
0.50
article

MyUEVision: an application generating image caption for assisting visually impaired people

Thai Huynh, Nha Tran, Hung Tan Nguyen, Toan Nguyen
article en
2 citations

Abstract

Purpose Visually impaired people usually struggle with doing daily tasks due to a lack of visual cues. For image captioning assistive applications, most applications require an Internet connection for the image captioning generation function to work properly. In this study, we developed MyUEVision, an application that assists visually impaired people by generating image captions that can work with and without the Internet. This work also involves reviewing some image captioning models for this application. Design/methodology/approach The author has selected and experimented with three image captioning models for online models and two image captioning models for offline models. The user experience (UX) design was designed based on the problems faced by visually impaired users when using mobile applications. The application is developed for the Android platform, and the offline model is integrated into the application for the image captioning generation function to work offline. Findings After conducting experiments for selecting online and offline models, ExpansionNet V2 is chosen for the online model and VGG16 + long short-term memory (LSTM) is chosen for the offline model. The application is then developed and assessed, and the results show that the application can generate image captions with or without the Internet, providing the best result when having an Internet connection, and the image is captured in good lighting with a few objects. Originality/value MyUEVision stands out for its both online and offline functionality. This approach ensures the image captioning generator works with or without the Internet, setting it apart as a unique solution to address the needs of visually impaired individuals.

Journal of Enabling TechnologiesVol. 18(4)
Ho Chi Minh City University of Education (VN)
Openalex Percentile: Top 36%
Multimodal Machine Learning Applications
0.50
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MyUEVision: an application generating image caption for assisting visually impaired people — Thai Huynh, Nha Tran, et al. · Journal of Enabling Technologies (2024) | TGRS Research Map | TGRS