G. Anna Lakshmi

Work place: Manonmaniam Sundaranar University, Tirunelveli, India

E-mail: annalakshmi.msu@gmail.com


Research Interests: Data Structures, Data Structures and Algorithms, Data Compression, Medical Image Computing, Image Processing, Image Manipulation, Image Compression


G.Anna Lakshmi has completed her M. Tech in Computer Science and IT from CITE, Manonmaniam Sundaranar University, Tirunelveli, Tamilnadu, India. she has more than 14 years of teaching experience and guided handful of projects both at U.G and P.G level at various applications like Image Processing, Image retargeting, Web based application and wireless sensors. She is pursuing her Doctorate in Philosophy in Computer Science and Engineering at Manonmaniam Sundarnar University, Tirunelveli, Tamilnadu, India. She is presently working as Senior Professor in Department of Computer Science and Engineering, Kamaraj College of Engineering and Technology ,Virdhunagar, Tamilnadu , India Since 2008. Her research interest includes Medical Image Processing, Image Retargetting, Data Science &Data analytics wireless sensors. She is a Life member in ISTE, and Computer Society of India.

Author Articles
A Double Layered Segmentation Algorithm for Cervical Cell Images based on GHFCM and ABC

By G. Anna Lakshmi S. Ravi

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.

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