FabriFit - Smart Stitch Advisor

Abstract

The rapid growth of the fashion and textile industry has increased the demand for intelligent systems that assist 
users in making informed clothing decisions. This project proposes FabriFit, an AI-based mobile application that 
automatically identifies fabric types from uploaded cloth images and helps users select cost-effective clothing 
options. The system utilizes Artificial Intelligence (AI), Machine Learning (ML), and Convolutional Neural 
Networks (CNNs) to analyze fabric textures and classify them into categories such as cotton, silk, wool, rayon, 
and other textile materials. AI-driven image analysis provides an efficient method for recognizing textile patterns 
and attributes, enabling automated fabric identification while reducing the need for manual inspection. 
In addition to fabric classification, the application estimates the required cloth length for stitching using user 
body measurements such as height and weight. Based on fabric costs and tailoring charges, the system performs 
a comparative analysis between ready-made garments and custom-stitched clothing, allowing users to identify 
the most economical option. By integrating fabric recognition, cost estimation, image classification, and a user
friendly mobile interface, FabriFit functions as an intelligent fashion assistant. The proposed system enhances 
customer decision-making, minimizes unnecessary expenditure, and promotes smarter clothing purchases in the 
modern digital fashion ecosystem.