Automatic Fabric Fault Detection Using Image Processing

This paper provides an overview of automatic fabric fault detection approaches that have been developed in recent years. Fabric fault detection is very popular topic of automation moreover quality control is one of the important features in textile industry. The performance of the projected idea is evaluated by using different techniques of patterned fabric images with different types of common fabric defects. Moreover detection methods were also evaluated in real time using a model automation specification system. This research paper will be useful for both researchers and practitioners in the field of image processing and computer vision to understand the uniqueness of the different defect detection methods. The recognition receives a digital fabric image from the image acquisition device and transforms it to a binary image using the restoration and threshold methods. This research presents a technique that decreases physical exertion. This image processing method was performed using "MATLAB 7.10". Therefore, this study uses a textile fault detector with a systematic vision approach for image processing.