Quality inspection is an important aspect of modern industrial manufacturing. In textile industryproduction, automate fabric inspection is important for maintain the fabric quality. For a long time the fabricdefects inspection process is still carried out with human visual inspection, and thus, insufficient and costly.Therefore, automatic fabric defect inspection is required to reduce the cost and time waste caused bydefects. The development of fully automated web inspection system requires robust and efficient fabricdefect detection algorithms. The detection of local fabric defects is one of the most intriguing problems incomputer vision. Texture analysis plays an important role in the automated visual inspection of textureimages to detect their defects. Various approaches for fabric defect detection have been proposed in pastand the purpose of this paper is to categorize and describe these algorithms. This paper attempts to presentthe survey on fabric defect detection techniques, with a comprehensive list of references to some recentworks. The aim is to review the state-of-the-art techniques for the purposes of visual inspection and decisionmaking schemes that are able to discriminate the features extracted from normal and defective regions.Therefore, on the basis of nature of features from the fabric surfaces, the proposed approaches have beencharacterized into three categories; statistical, spectral and model-based.