MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641081090 A) filed by Mlr Institute Of Technology on July 01, 2026, for Ai-Driven Fashion Recommendation System Using Text And Image Analysis.
Inventors include Mrs. B. Veda Vidhya; Ms. Bollagani Reshma; Ms. P. Sasi Madhuri; and Mr. P. Ajay.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: In this invention, “AI-Driven Fashion Recommendation System Using Text and Image Analysis” is disclosed as an intelligent recommendation framework designed to provide personalized fashion suggestions by integrating computer vision, artificial intelligence, machine learning, and natural language processing techniques. The invention enables users to upload fashion images and provide textual inputs describing their style preferences, clothing requirements, fashion interests, occasions, and aesthetic choices. An image preprocessing module enhances and standardizes the uploaded images before they are analyzed by an AI-based image analysis engine. The image analysis engine extracts visual attributes including garment category, color, texture, pattern, fabric characteristics, style elements, and design features. Simultaneously, a natural language processing module analyzes textual information to identify user preferences, fashion trends, style intentions, and contextual requirements. The extracted visual and textual features are transformed into structured feature vectors and stored within a feature database containing information related to fashion products, user profiles, and recommendation histories. A similarity computation engine compares the extracted features with stored fashion items using similarity measurement techniques such as cosine similarity, feature matching, embedding analysis, and machine learning- based ranking methods. Based on the computed similarity scores, the system generates personalized recommendations comprising clothing items, accessories, footwear, coordinated outfits, and styling suggestions. The invention further incorporates adaptive learning mechanisms that continuously refine recommendations using user interactions, purchase history, ratings, browsing behavior, and feedback data. Trend analysis capabilities may also be integrated to ensure that recommendations remain aligned with current fashion trends and consumer preferences. The proposed system can be deployed across e-commerce platforms, online retail applications, virtual styling assistants, and fashion advisory services. By integrating image analysis, text understanding, feature extraction, similarity computation, adaptive learning, and personalized recommendation generation within a unified framework, the invention significantly improves recommendation accuracy, enhances customer engagement, simplifies fashion discovery, supports informed purchasing decisions, and advances intelligent fashion retail technologies.
Disclaimer: Curated by HT Syndication.
