Taguchi's Design of Experiments was applied to determine the effect of Fused Deposition Modeling (FDM) parameters such as layer thickness, infill density, and infill line thickness and deposition pattern on surface roughness. Nylon material was fused to produce samples. Conventional probe surface area measurements were performed to extract the Ra values of the samples. Subsequently, the non-contact measurement of 3D printed textures using the Gray Level Co-Occurrence Matrix (GLCM) algorithm was introduced through image processing. The FDM-printed surface image parameters such as correlation and homogeneity are Ra responsive and therefore a signal-to-noise ratio (S/N) analysis was performed to identify optimal parameters. A slight, unexplained deviation in surface image parameters was detected, and this inaccurate deviation may be due to image noise, image distortion, and different lighting associated with capturing and processing printed surface images. The result of the analysis shows that a good surface quality is achieved if a layer thickness of 0.2 mm, 100% bulk density and 1.0 mm bulk thickness are selected. When optimal parameters were reached, the FDM print was repeated and then the results were validated to ensure the accuracy of the method used. The results obtained in the present study could be proposed in the field of additive manufacturing, which improves the surface quality of the FDM sample.