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Abstract
The PCOS( polycystic ovary syndrome ) in females is a disease that is regulated by genetic and other environmental factors. For identifying this type of disease, genes are needed and it is difficult to detect. In the proposed work the medical image processing is utilizes to detect PCOS disease from different type of images. Medical image processing can improve detection of small cysts in females by mixing and merging of various image segmentation techniques. In the proposed algorithm the detection of disease is done using two phases: extraction and classification .the results show that it will improve the accuracy and give better prediction. Region of interest methods give best results having overall accuracy of 89% and F1 score of 85%.