Fabric inspection is important for maintaining the quality of fabric. Traditional inspection process for fabric defects is human visual inspection which is insufficient and costly. The quality inspection process for textile fabrics is mainly performed manually. About 70% of fabric defects could be detected by the most highly trained inspectors. In textile industry improved performance in the inspection of fabrics leads to good product quality and contributes to increased profitability and customer satisfaction. Hence the automatic fabric defect inspection is required to reduce the cost and time waste caused by defects. Therefore, automated detection of fabric defects, which results in the production of high-quality products at a high production speed is desirable. The detection of local fabric defects is one of the most problems in computer vision. To upgrade this process the fabrics when processed in textiles the fault present on the fabrics can be identified using MATLAB with Image processing techniques. These image processing techniques are applied using MATLAB and for the input image of a defective fabric, conversion into grey scale image, noise filtering, binary image conversion, histogram technique, thresholding are applied on the image and the output is obtained.