Analysis of Pixel Intensity Variation by Performing Morphological Operations for Image Segmentation On Cervical Cancer Pap Smear Image

Abstract

Cervical cancer is the second largely hazardous metastatic tumor that develops in a woman’s cervix. If it is detected at the premature stage and treated correctly then there can be less mortality ratio rate due to cervical cancer .In preliminary stage Pap smear is the simple scrutiny test generally used for the revealing of cancer. For precise screening and detection, cervical cancer is categorized as normal and abnormal cancer which includes the cell and cytoplasm in the identical structure. It is complicated task to distinguish a cancerous nucleus in the cell. Medical image processing is mainly significant but time consuming and complicated task. Medical Image preprocessing of cervical cancer pap smear images and its scrutiny is act of investigating images for recognizing objects and evaluating their impact. The primary reason of Image processing is for discovering of various kinds of unnecessary cells and exposing the amount it spreads. So for the precise segmentation of cervical cells in Pap smear image becomes an essential job to automatically identify the precancerous transforms in the cervix. Image segmentation basically refers to method of division of the image into several segments for tracing objects and borders in image. Various Image processing and segmentation algorithms are utilized to section the nucleus alone in microscopic images.The primary scope of this paper is to spotlight on how the morphological operations on cervical cancer pap smear images is achieved to fine-tune to appropriate pixel concentration and proper contrast for sorting out the tumor piece from an image. In the addressed proposed work morphological operations like erosion, dilation, opening, and closing are executed and implemented with the aid of structuring element entitled as kernel. Python libraries are used for implementation of proposed work. As the morphological transformation is applied, minimum and maximum pixel intensity is also been computed.