Work place: Dept. of CSE, Pondicherry University, Pondicherry, India
Research Interests: Detection Theory, Medical Image Computing, Image Processing, Intrusion Detection System, Image Manipulation, Pattern Recognition, Computer Vision, Medical Informatics
Dr. S. Ravi is now working as (Associate) Assistant Professor in the Department of Computer Science, School of Engineering and Technology, Pondicherry University, Pondicherry. He has 26 Years and 3 months of teaching experience and more than 11 years of research experience after his Post Graduate Degree in Technology. He has published more than 185 research papers in total, including 47 Scopus Indexed International Journals, 8 Springer Journal (Special Volume), 33 Other International Jouranals, 1 Elsvier Proceedia Computer Science, 7 Elsvier Journal Proceedings, 1 Springer Journal Proceedings, 1 IET Conference Proceedings, 1 IDES Conference Proceedings, 20 IEEE Conferences Proceedings, 42 International Conferences proceedings, 19 National Conferences Proceedings. He is a Senior Member of IEEE, Treasurer, IEEE SIPSHICOM, PODHIGAI Section, Member in IEEE Young Professionals, IEEE Computational Intelligence Society, IEEE Circuits and Systems Society, IEEE Sensors Council, IEEE Systems Council, IEEE Biometrics Council, IEEE Council on Electronic Design Automation, the Indian Science Congress and Life Member in Computer Society of India. His research interest includes Biometrics, Medical Imaging, Skin Detection, Face Detection, Face Recognition, Face Tracking, Computer Vision, Digital Image Processing.
DOI: https://doi.org/10.5815/ijigsp.2017.11.05, Pub. Date: 8 Nov. 2017
Cancer is a life threatening disease and it engulfs the lives of many women. Due to the technology advancement, the medical science is drastically improved. A statistical report claims that the diagnostic decisions of radiologists show more false positive rates, which is very dangerous. However, when the radiologists are supported by computer aided applications, the false positive results are considerably reduced. Understanding the potentiality of computer aided applications, this paper presents a double layered segmentation algorithm for cervical cell images. The entire work is subdivided into three important phases, which are cervical image pre-processing, coarse and fine level segmentation. The pre-processing phase attempts to remove the noise and enhance the image quality by means of adaptive mean filter and Contrast Limited Adaptive Histogram Equalization (CLAHE) technique respectively. The coarse level segmentation process is achieved by Generalized Hierarchical Fuzzy C Means (GHFCM) and the fine level segmentation process is carried out by Artificial Bee Colony (ABC) algorithm. The performance of the proposed segmentation algorithm is analysed in terms of accuracy, sensitivity and specificity. The experimental results show the efficacy of the proposed segmentation algorithm.[...] Read more.
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