Fiber optic interferometry has been used to detect small displacements in diverse applications. Counting the number of fringes in fiber-optic interferometry is challenging due to the external effects induced in dynamic systems. In this paper, a novel interference fringe counting technique is developed to convert the intensity of interference data into displacements in the range of micrometers to millimeters while simultaneously resolving external dynamic effects. This technique consists of filtering the rough experimental data, converting filtered optical interference data into displacements, and resolving dynamic effects of the experimental system. Filtering the rough data is performed in time by using the moving average method with a window size of 400 data points. Filtered optical data is further converted into displacement by calculating relative phase differences of each data point compared to local maximum and local minimum points. Next, a linear curve-fit is subtracted from the calculated displacement curve to reveal dynamic effects. Straightness error of the lead screw driven stage, dynamics of the stepper motor, and profile of the reflective surfaces are investigated as the external dynamic effects. Straightness error is characterized by a 9th order polynomial function, and the effect of the dynamics of the stepper motor is fitted using a sinusoidal function. The remaining part of the measurement is the effect of roughness and waviness of the reflective surfaces. As explained in the experimental setup part, two fiberoptic probes detect the vertical relative displacements in the range of 1-50 mu m, and the encoder probe detects 13.5 mm horizontal displacement. Thus, this technique can detect three order of magnitude different dynamic displacements with sub-micrometer resolution. The current methodology can be utilized in different applications which require measuring straightness error of lead-screw driven stages, large area surface profile of specimens, and vibration of actuators such as stepper motors. (C) 2016 Elsevier Ltd. All rights reserved.