Multilevel thresholding is a popular method for dividing images into different parts. Unlike simple thresholding, which uses only one value, multilevel thresholding uses multiple values to get better results, especially for complex images. However, finding the right threshold values can be tricky and time-consuming. To solve this, researchers have developed automatic techniques that use special algorithms to pick the best thresholds. These algorithms help speed up the process and make it more accurate. The researchers in this article looked at different ways to automatically choose threshold values and compared how well different algorithms work for this task. They also talked about how to test these methods and mentioned some ways this technique can be used in real life.