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| 005 | 20250920173758.0 | ||
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_e _e _aBanez, Crystal Mae M., Poso, Raseck Kiel D., Tavas, Ella Micca B. _d _b4 _u _c0 _q16 |
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_a _aForhue: an assistive mobile application for color - blind individuals using KNN algorithm. _d _b _n _c _h6 _p |
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_3 _30 _b _aunmediated _2rdamedia |
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_a _aUndergraduate Thesis (BS in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2023. _d _b _c56 |
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_b _b _c _aABSTRACT: In this research project, color blindness, a worldwide occurrence and the most common type of blindness, hs been chosen as the subject. It is a condition in which an individual has difficulty seeing accurate hues. This poses a problem for color-blind individuals, especially younger ones, whenever they travel or engage in activities that require distinguishing colors. For instance, identifying the colors of fruits and toys for younger color-blind individuals while encountering traffic lights on the road or distinguishing color-coded signs for the majority of color-blind people can be stressful or burdensome. As a result, the researchers felt motivated to develop a mobile application that identifies colors for color-blind individuals. The paper was titled ForHue: An Assistive Mobile Application for Color-Blind People Using KNN Algorithm. It utilizes the KNN algorithm Weka Java API for color recognition and OpenCV for camera access in the Java-based mobile application. The datasets use K+1 as the K-value in Camera Live Portion and K=5 as the K-value in Upload Portion. The application meets the project's goals, including 1) using the KNN algorithm and OpenCV for color detection; 2) assistive features such as TTS, several camera settings (pause, resume, flip, resolution), crop implementation in upload part and color naming; and 3) Compliance with ISO 9241-11's standards. Our project provides solutions to our problem statement as a result. With a score of 71.67, the SUS survey revealed that the application met the ISO standard for effectiveness, efficiency, and satisfaction with a good rating. _u |
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