Background subtraction, a procedure required in many video analysis applications such as object tracking , is dependent on the model background image. One efficient algorithm for background image generation is the Teknomo-Fernandez (TF) Algorithm, which uses modal values and a tournament-like strategy to produce a good background image very quickly. A previous study showed that the TF algorithm can be extended from the original 3 frames per tournament (T F 3) to T F 5 and T F 7, resulting in increased accuracies at a cost of increased processing times. In this study, we explore extending the T F 3, T F 5 and T F 7 from the original RGB colour space to the HSV colour space. A ground truth model background image for HSV was also developed for comparing the performances between the TF implementations on the RGB and HSV channels. The results show that the TF algorithm generates accurate background images when implemented on the HSV colour space. However, the RGB implementations still exhibit higher accuracies than the corresponding HSV implementations. Finally, background subtraction was applied on the HSV generated background images. A comparison with other promising baseline techniques validates the competitiveness of the TF algorithm implemented on HSV channels.