In electrical impedance tomography (EIT), a fundamental challenge arises in discerning objects with similar conductivities situated close to each other, as well as distinguishing highly conductive objects positioned farther from the electrodes within the imaging domain. This underscores the need for optimized techniques to accurately differentiate between such objects, thereby enhancing the utility of EIT in various applications. The experiments were designed to evaluate the effectiveness of different frequency ranges, specifically the alpha range that encompasses 5 and 10 kHz, and the beta range that includes 20 kHz, 50 kHz, and 100 kHz. These frequencies were chosen on their potential to differentiate materials with varying conductivities. The experiments used the Contrast-to-Noise Ratio (CNR) as a key metric to assess discrimination capabilities. The results of the experiments indicate that frequencies ranging from 40 kHz to 80 kHz are particularly adept at accentuating conductive objects against the background, achieving a CNR normalization threshold exceeding 0.9. This finding corroborates previous research and underscores the efficacy of selecting appropriate frequency ranges for selecting materials with distinct conductivities. The optimized frequency range identified in this study significantly contributes to the refinement of EIT-based imaging techniques. By enhancing the ability to detect and characterize objects in dynamic environments, particularly those that require differentiation based on dispersion behaviors, these findings have substantial implications for a wide array of applications. Further exploration of frequency optimization and its integration into EIT methodologies promises to advance the understanding and utilization of this imaging modality in diverse fields.