Classification of Microscopic Cervical Cancer Images using Regional Features and HSI Model
Robert P1, Celine Kavida A2
1Robert P, Research Scholar, Department of Information Technology, Vel Tech Multi Tech, Dr. Rangarajan, Dr. Sakunthala Engineering College, Chennai (TamilNadu), India.
2Celine Kavida A, Associate Professor, Department of Physics, Vel Tech Multi Tech, Dr. Rangarajan, Dr. Sakunthala Engineering College, Chennai (TamilNadu), India.
Manuscript received on 05 June 2019 | Revised Manuscript received on 12 June 2019 | Manuscript Published on 19 June 2019 | PP: 24-28 | Volume-8 Issue-8S June 2019 | Retrieval Number: H10050688S19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The main purpose of this paper is to classify the microscopic cervical images in order to identify the true impact of cancer that helps the patient to be treated properly. The Pap smear test is most efficient medical test, but it generates problem at the time of interpretation under the microscope. In order to unravel this drawback, automatic cancer detection is developed. This detection process includes few techniques of the image processing such as segmentation, and enhanced SVM classification algorithm. The final outcome of this proposed technique is compared to previous classification techniques such as ANN (Artificial Neural Network), KNN (K-Nearest Neighbor). The proposed algorithm is found to yield a good result from the experimental results & performance evaluation.
Keywords: Cervical Cancer, Microscopic Images, Classification, CIN.
Scope of the Article: Classification