Microwave ablation has emerged as a promising technique to treat bone tumors, offering a minimally invasive alternative to traditional methods. Accurate segmentation and quantification of ablated zones are essential to evaluate the MWA technique; firstly, when new antennas are proposed. Moreover, the use of conventional medical imaging systems such as CT or MRI is often unavailable during early experimental stages due to their high cost. Therefore, this study proposes an automatic image segmentation method based on the combination of RGB and CIELab color spaces to segment ablation areas in ex vivo porcine bone treated with microwave ablation. The proposed method enhances chromatic differences between healthy and ablated tissue by integrating the a* channel of the CIELab space with the red channel of the RGB space, generating a composite image. A threshold of 0.35, determined by using the intensity histogram, was applied to the enhanced image to create a binary mask. Connected component labeling was used to identify individual ablation regions, enabling precise calculation of ablation areas at different tissue depths. Results show a strong correlation between tissue color, temperature, and ablation zones, confirming the method’s efficacy in characterizing spatial thermal effects. Compared to conventional segmentation techniques such as Otsu and Canny, the proposed method offers superior performance in detecting ablation zones. Ablation areas calculated were 8.6 cm2, 7.2 cm2, and 6.4 cm2 at 0 mm, 3 mm, and 6 mm, respectively, from the antennas by using 20 W per antenna for 20 min.