M.Tech Skin Tone Based Clothing Recommendation Final Year PHP Project Report

Skin Tone Based Clothing Recommendation System is a complete Core PHP and MySQL fashion e-commerce application that helps shoppers discover clothing colours and outfit combinations suited to their skin tone and undertone.

The project combines a public fashion storefront, authenticated customer panel, and separate Admin Panel. Customers can create a skin profile manually or use local photo analysis, view Best Match, Good Match, and Regular Match clothing-colour recommendations, build outfit combinations, manage wishlist and cart, place Cash on Delivery orders, track order status, and review delivered products.

The recommendation system is rule-based. Product colours are matched against configurable skin-tone and undertone rules using HEX/RGB colour-distance logic stored in MySQL. Optional skin-tone detection is performed locally using the PHP GD extension, so the application does not require an external AI, computer-vision, recommendation, payment, or shipping API.

Administrators manage brands, categories, products, colour and size variants, inventory, skin-tone categories, undertones, colour rules, outfit rules, orders, users, reviews, homepage content, website settings, and operational reports.

This project is suitable for B.Tech, M.Tech, BCA, MCA, BE, ME, BSc, MSc, Computer Science, IT, PHP, MySQL, E-Commerce, and Web Development students looking for a final year project, major project, minor project, source code, and project report based on personalized fashion recommendations, skin-tone analysis, outfit matching, clothing e-commerce, and inventory management.