  Image Segmentation is a technique of partitioning the original image into
some distinct classes. Many possible solutions may be available for segmenting
an image into a certain number of classes, each one having different quality of
segmentation. In our proposed method, multilevel thresholding technique has
been used for image segmentation. A new approach of Cuckoo Search (CS) is used
for selection of optimal threshold value. In other words, the algorithm is used
to achieve the best solution from the initial random threshold values or
solutions and to evaluate the quality of a solution correlation function is
used. Finally, MSE and PSNR are measured to understand the segmentation
quality.
