Fabric Color and Design Identification for Vision Impaired

Abstract

Abstract - The weave pattern (texture) of woven fabric is considered to be an important element in the design and production of high-quality fabric. Traditionally, the recognition of woven fabric has many challenges due to its visual cues made by hand. In addition, methods based on pre-machine learning algorithms depend directly on manual features, which are timeconsuming and erroneous processes. Therefore, the default system is required to be divided into layers of woven fabric to improve productivity. In this paper, we propose an in-depth study model based on data extraction and a transfer method for the separation and recognition of woven fabrics. The model uses a residual network (ResNet), where the fabric texture features are automatically extracted and segmented in a way that ends. We tested the results of our model using test metrics such as accuracy, approximate accuracy, and F1 score. Keywords – Artificial intelligence, color, design, fabric and image processing