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@article{186640,
        author = {Dr. S. Jeyalakshmi and M. Abinaya and M. Abiraj and A. Dharaneesh},
        title = {Tone 2 Style- Skin Tone Detection For Personalized Color And Outfit Recommendation},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {4327-4333},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=186640},
        abstract = {Many individuals struggle to choose clothing colors that complement their skin tone, often resulting in poor fashion choices, wasted expenditure, and reduced self-confidence. In the absence of easy-to-use tools for personalized color guidance, most people rely on guesswork or generalized fashion advice that may not suit everyone. This project presents a smart web application that employs image processing to analyze skin tones and recommend the most suitable dress colors based on the user’s gender and occasion. Users simply upload their photograph through an intuitive interface, after which the system automatically detects the face using OpenCV and analyzes skin color using HSV and RGB models. The application categorizes skin tones into three types warm (golden or peachy shades), cool (pink or blue shades), and neutral (balanced tones). Based on user inputs such as gender (male or female) and event type (party, wedding, or vacation), the system selects ideal color and outfit recommendations from a dataset containing 108 color samples and 54 outfit ideas. Developed using Flask for backend processing and modern web technologies (HTML, CSS, JavaScript) for an interactive frontend, the system delivers smooth navigation with animated, clickable cards. For males, the tool suggests formal wear such as suits and sherwanis, while for females it recommends dresses, sarees, and lehengas matched to their tone and occasion. The results include color samples with hexadecimal codes, outfit descriptions, accessory suggestions, and practical styling tips on favorable and unfavorable shades. Unlike other fashion applications requiring extensive user input, this system provides instant, accurate results through automated face detection and color analysis. By combining computer vision with a structured fashion database, TONE 2 STYLE offers accessible, professional styling recommendations that help users shop smarter and feel more confident. Future enhancements include the addition of new colors, event categories, and advanced features such as improved tone detection and virtual try-on capabilities.},
        keywords = {Color recommendation, Computer vision, Flask, Fashion technology, HSV and RGB color models, Image processing, OpenCV, Personalized styling, Skin tone detection},
        month = {November},
        }