Publicação
Automated garment recognition and assessment system using computer vision and artificial intelligence for blind people
| Resumo: | Clothing management is one of the most significant challenges faced by blind and visually impaired people. By leveraging advanced technologies, such as computer vision and artificial intelligence (AI), this PhD work aimed at developing and validating a mechatronic device, the iSight prototype, able to assist in the identification of clothing types, colours, and conditions, primarily designed for blind and visually impaired users. Valuable insights were obtained from a nationwide survey, conducted in collaboration with the Association of the Blind and Amblyopes of Portugal (ACAPO), which revealed a high demand for technological solutions in garment management, with 95.7 % of respondents expressing willingness to adopt new technologies. The iSight prototype integrates a smart wardrobe equipped with an image acquisition system and controlled lighting, ensuring optimal image quality capture for accurate analysis. The device is controlled via a user-friendly mobile application, designed to be highly accessible and intuitive. The system's functionality was rigorously tested with 15 participants from ACAPO, encompassing both blind and low-vision people. The prototype's accuracy in identifying clothing categories and colours was highly acknowledged by users, with 60 % finding it very precise in identifying categories and 80 % in identifying colours. Additionally, 86.7% of participants rated the system's ability to detect stains and identify Near Field Communication (NFC) tags as highly effective. Finally, the obtained results demonstrated high levels of user satisfaction. Extensive statistical analyses confirmed significant positive correlations between the iSight functionalities and in users' confidence, self-esteem, well-being, and independence. These findings highlight the prototype's potential to significantly enhance the daily lives of visually impaired people. Key areas for further improvement were also identified by the users, namely the reduction of menu complexity and addition of detailed fabric information. In conclusion, this PhD work demonstrates the feasibility and effectiveness of integrating computer vision and AI technologies into a mechatronic device (smart wardrobe) to support blind and visually impaired people in garment identification and management. The iSight prototype offers a robust and user-friendly solution that significantly improves users' quality of life, offering room for future refinement and paving the way towards a truly disruptive product for smart and effective clothing management. |
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| Autores principais: | Rocha, Daniel Filipe Coelho |
| Assunto: | Artificial Intelligence (AI) Assistive Technology Blind People Clothing Identification and Modifications Computer Vison Mobile Application Smart Wardrobe Aplicação Móvel Guarda-Roupa Inteligente Identificação e Modificação de Roupa Inteligência Artificial (IA) Pessoas Cegas Tecnologia Assistida Visão Computacional Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | tese de doutoramento |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | Clothing management is one of the most significant challenges faced by blind and visually impaired people. By leveraging advanced technologies, such as computer vision and artificial intelligence (AI), this PhD work aimed at developing and validating a mechatronic device, the iSight prototype, able to assist in the identification of clothing types, colours, and conditions, primarily designed for blind and visually impaired users. Valuable insights were obtained from a nationwide survey, conducted in collaboration with the Association of the Blind and Amblyopes of Portugal (ACAPO), which revealed a high demand for technological solutions in garment management, with 95.7 % of respondents expressing willingness to adopt new technologies. The iSight prototype integrates a smart wardrobe equipped with an image acquisition system and controlled lighting, ensuring optimal image quality capture for accurate analysis. The device is controlled via a user-friendly mobile application, designed to be highly accessible and intuitive. The system's functionality was rigorously tested with 15 participants from ACAPO, encompassing both blind and low-vision people. The prototype's accuracy in identifying clothing categories and colours was highly acknowledged by users, with 60 % finding it very precise in identifying categories and 80 % in identifying colours. Additionally, 86.7% of participants rated the system's ability to detect stains and identify Near Field Communication (NFC) tags as highly effective. Finally, the obtained results demonstrated high levels of user satisfaction. Extensive statistical analyses confirmed significant positive correlations between the iSight functionalities and in users' confidence, self-esteem, well-being, and independence. These findings highlight the prototype's potential to significantly enhance the daily lives of visually impaired people. Key areas for further improvement were also identified by the users, namely the reduction of menu complexity and addition of detailed fabric information. In conclusion, this PhD work demonstrates the feasibility and effectiveness of integrating computer vision and AI technologies into a mechatronic device (smart wardrobe) to support blind and visually impaired people in garment identification and management. The iSight prototype offers a robust and user-friendly solution that significantly improves users' quality of life, offering room for future refinement and paving the way towards a truly disruptive product for smart and effective clothing management. |
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