The hair-counting technique using photosensors is a common method to measure the hairiness of the yarns. However, the literature recognizes some deficiencies of the technique regarding the sensor limitations. This paper describes a computer vision approach to simulate the photosensors and to investigate the parameters effecting the hairiness measurement when using these sensors. An algorithm developed to simulate the photosensor signals is explained. The effects of sensor resolution, signal threshold level and selection of zero reference positions from the core are investigated. The correlation between the measurements taken from two different sides of the yarn core is also examined. Twenty yarn samples are tested using a Zweigle G565 hairiness tester, and the results are compared with the hairiness measurements from the simulated photosensor system using digital images.