The Selective Laser Melting (SLM) process based additive manufacturing has wide applications in medical, aerospace, defense, and automotive industries. To qualify the components for certain tribological applications, the characterization of surface texture is very important. But the applicability of traditional methods and parameters to characterize the surface texture were under evaluation. As the nature manufacturing the components were very different and complex, the unconventional surface characterization methods also under evaluation to reveal much more meaningful information. This study demonstrates the surface characterization of Ti-6Al-4V SLM components using fractal analysis of the surface images. The computed fractal dimension using the Fourier transform method showed a strong correlation of more than 0.8 with the measured 3D surface roughness parameters. The change in anisotropic nature of the surface images with the process parameter variation is studied and found that the surface textures showed a weaker anisotropic nature at lower laser power ranges, high scanning speed, and high hatch distance values. The lacunarity analysis is carried out using the gliding box algorithm to study the homogeneity nature of the surface texture and found that the surface texture is more homogeneous at higher surface roughness conditions. The study results can be utilized for the development of a quick, low-cost surface monitoring system in real-time for additive manufacturing industries.