L. Malliga

Work place: M.Kumarasamy College of Engineering, Karur, India

E-mail: malligamkce@mkce.ac.in

Website:

Research Interests: Image Compression, Image Manipulation, Image Processing, Medical Image Computing, Information Retrieval

Biography

L.Malliga received diploma, Electronics and Communications Engineering from AyyaNadar Janakiammal Women’s college,Sivakasi in 1986.After the long break, she completed her AMIE, Electronics and Communications Engineering in 2006, the M.E Applied Electronics from RVS College of Engineering Dindigul in 2009.When she is currently pursuing the Ph.D(Part Time) in the Department of ECE and nearly twenty years of Teaching experience in various Polytechnic colleges and ITI’s.Now she is a Senior Assistant Professor in M.Kumarasamy college of Engineering,Karur.

She has published several National and Inter National conferences. She is a Life member of ISTE.Her major fields of interests are Content based Image Retrieval,Bio Medical Imaging and Wavelet Transform.

Author Articles
Multiple Ranks Weighting Score for Microscopic Image Retrieval System

By P. Suresh L. Malliga M. Vijay

DOI: https://doi.org/10.5815/ijitcs.2014.10.06, Pub. Date: 8 Sep. 2014

Content based medical images have become a major necessity with the growing retrieving Advancements. CBIR access to medical images for supporting clinical decision making has been proposed that would be ease to manage large number of image in the database system. [4] In real time case only few systems has been developed and used in clinical environment. Content-Based Image Retrieval refers to image retrieval system that is based on visual properties of image objects other than textual annotation. Query image features compare with the database image features which is not exactly matching so image feature can be compare with the two tier approach in the database image in order to improve the accuracy of the retrieval system. Every day, large volume of different types of medical images such as MRI, CT images ultrasound, x-ray, radiology, etc are produced in different medical centre’s .microscopic image classification and discrimination (sub-type) [12] is the most difficult problem in medical image retrieval system. In this paper, the survey provides the suitable algorithm for retrieval and classification of medical image to improve the overall accuracy of the MIMS.

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