The research was conducted with the main purpose of developing a proposed algorithm; Charlotte Ama Mensah Segmentation Algorithm (CAMSEG) that combines K-Means and PSO clustering algorithms under the supervision of the Otsu Algorithm, which acts as the intelligent part of the algorithm to find the threshold value of an image and with respect to the threshold value, the CAMSEG algorithm selects one of the two algorithms to start the optimization process and will complete the process with the other algorithm (that is, either KM/PSO or PSO/KM).The study makes use of the JAVA programming language to implement the following five algorithms; K-Means, PSO, hybrid K-Means PSO, hybrid PSO K-Means and CAMSEG. The CAMSEG algorithm is suggested because the K-Means algorithm works best with images whose threshold values are less than or equal to 180 and so based on this the CAMSEG algorithm chooses to begin the segmentation process with K-Means for all images with threshold value less or equal to 180.This is done by using the Otsu?s algorithm to find the threshold value of the image, then based on the threshold value, the algorithm chooses which of the two algorithms to begin the segmentation with. After testing all algorithms with sample images, the general implication is that, it is possible to allow one hybrid algorithm to automatically decide which of the two algorithms K-Means or PSO to start the segmentation process with and end with the other algorithm. It has therefore been concluded that not all images can be conveniently segmented with either hybrid KM/PSO or PSO/KM to give effective results since images have different threshold values.