A Novel Method to Authenticate Texture of Cotton and Silk Saree Using Image Processing & RCNN Machine Learning Techniques

The popularity of sarees, as Indian traditional garment, is spreading all over the world, and because of their variety and different type of materials used in making traditional garment need to automate and classification methods are required to identify best among the existing. This work offers a novel method for classifying and detecting saree types using computer vision techniques. The visual features of sarees are classified by using image processing with machine learning models as preprocessing to improve the classification model. With the use of region based CNNs texture feature will be extracted and identification of different types of material used (Silk/Cotton/Shiffon). The provided material and its category plays a vital role in differentiating Kanchivaram Silk Sarees. The model ensures stability across datasets and training conditions, as demonstrated by experimental findings that show its improved accuracy and speed over using traditional deep learning techniques. This research increases computer vision in apparel recognition and categorization with applications in e-commerce and fashion recommendation.