<![CDATA[Color blindness is a hereditary vision disorder that impairs the ability to distinguish certain colors, significantly affecting daily activities and quality of life. This study aims to develop a web-based application using Flask and OpenCV to assist individuals with color blindness in identifying colors accurately. The application incorporates image processing technology to enhance color contrast and simulate real-time color perception adjustments. Employing the Waterfall model of the Software Development Life Cycle (SDLC), the study encompasses requirements analysis, system design, implementation, testing, and maintenance. Key features include Camify, for real-time color adjustments via device cameras, and Pickerify, for detecting colors in uploaded or live images. Testing reveals the application's effectiveness in providing improved color perception for users with various types of color blindness (e.g., Deuteranopia, Protanopia, Tritanopia). Despite minor limitations under extreme lighting conditions, the intuitive user interface and robust functionality make the application accessible to diverse user groups. Future enhancements include integrating AI for personalized filters and expanding compatibility with emerging technologies.]]>
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