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Abstract
Cancer of Cervical is one of the most widespread cancer form in world. As per WHO cervical cancer is the fourth most widespread form of cancer affecting women throughout the world and its early detection can help in saving life. Automated classification and diagnosis of cervical cancer is very importantrequirement as it allows timely,precise and consistentstudy of thepatient’shealth progress. This survey paper represents an outline of current research going in the field as presented or discussed in numerous research publications on automated classification and diagnosis of cervical(cervix) cancer from Pap smear images. Few of the techniques which include early detection of cervical cancer are segmentation, classification,from Medical Imaging, Machine Learning. The study revealed that some methods or techniques are used more commonly than others: for example thresholding, filtering, KNN and SVM are the most widely exploredmethods for pre-processing, segmentation, filtering and classification of images based on pap-smear. It has been observed that the outcomes based on classification and segmentation algorithms also depends on various other factors as well.