In recent years with the development of science, technology and considering the competitive market of textile industry, quality control, quantitative and qualitative measurement of yarn parameters, and prediction of the final products’ properties have found high importance. Nowadays, manufacturing companies are looking for computer vision and different algorithms for image processing as these methods do not need any complex and expensive devices)i.e. just by using a computer and a camera) and highly accurate results with low assessment errors can be obtained in a short time. In this study, the research works fon measuring the yarn parameters such as diameter, yarn hairiness, yarn twist, percent of wave in textured yarn, mixture percent in multi-member fibers, covering defect of core fibers, bulks of air-jet textured yarn, changing the shape of the fiber cross section in yarn and fiber defects using image processing are reviewed.