• Networks
• Network Security
• Wireless Sensor Networks
• Vehicular Adhoc Networks
• Cloud Computing
• IOT
• Cognitive Radio Networks
1. Dr.B.Guruprakash
2. Dr.V.Shanmugavel
3. Dr.G.Vairasuganthi
4. Dr.R.Rubesh Selvakumar
• An Adaptive Neuro Fuzzy Framework for Detection and Measurement of Phishing Attacks.
• Implementation of Environment Parameters Monitoring in a Manufacturing Industry Using IOT.
• A Secure Gateway for Tracing Files in Cloud Environment.
• Detection of Embezzlement of Real Currency Through Virtual Currency.
• Cipher Mail Server for Intranet.
• Recommendation Engine in Social Network Without Exposure Of Privacy.
• Biometric Encryption in Cloud Computing.
• An Effective Cluster Based Underwater Communication.
• Semantic Clustering Based Deep Hyper graph Model For Online Review in Cypher- Physical- Social- Systems.
• A Secure Hash Key Based Routing With PSO Efficient Data Aggregation in Wireless Sensor Networks.
• Finger Vein Based Authentication Approach Using Structure Analysis.
• Monitoring Indoor Air and Water Quality by Using IOT.
• Sparse Based Attack Detection in Cognitive Network.
• A Wireless Tracking System Using Location Prediction And Dynamic Thresholding.
• Internet of Things Enabled Fire and Gas Detection System for Safety Environment.
• IoT based health care systems.
• The Centre for Research in Image Processing is a research facility in the Department of Computer Science and Engineering established with the focus towards the areas of Image Processing, Medical Image Processing, Satellite Image Processing, Content based Image Retrieval, Pattern Recognition, Data Mining, Web Mining, Data Science and Analytics, Artificial Intelligence and Machine Learning. This lab is dedicated to find out the solutions for the problems in image processing applications by implementing the appropriate technologies like Data Mining , Machine Learning etc.,. The following research work has been carried out in this laboratory
• Content based image retrieval.
• Facial Recognition.
• Image Restoration.
• Classification of breast cancer.
• Change detection using Satellite Image Processing.
• Classification of satellite images.
• Analyzing Atherosclerosis Pathology in Fundal Images.
• Detecting melanomas in Digital Dermoscopy Images.
• Image Fusion Framework for Pathology localization.
• Computer Aided Bleeding Detection for Endoscope Images.
1. Dr.S.Siva Ranjani
2. Dr.M.Parvathy
3. Dr.R.Rubesh Selvakumar
4. Dr.K.Nagalakshmi
5. Dr.B.Lalitha
6. Mrs.M.Mathina Kani
7. Mrs.S.Selvi
8. Mrs.K.Krishnaveni
9. Mrs.S.Asha
10. Mrs.D.Suriya
• SVM Trained Fast Smoke Detection Method for UAV Images.
• Image Enhancement in Microscopic Images for Early Detection of Skin Cancer.
• An Effective Cluster based Underwater Communication.
• Development and Analysis of Rainfall Prediction using Data Mining Techniques.
• High Dimensional ICU Mortality Prediction using Big Data.
• An Enhancing Image Steganography Model for Secure Covert Communication.
• A Novel Image Encryption Algorithm using Chaotic Equation.
• Watermarking in Color Images using Genetic Algorithm.
• Automatic Face Naming by Affine Transformation with Two Dimensional Principal Component Analysis.
• Brain Tumor Detection using a New Segmentation Technique of SVM.
• Comparative Analysis of Local Binary Pattern Variants for the Retrieval of Texture and Color Images.
• Text-Based Binary Image Stylization and Synthesis and Position Estimation of Text in Images.
• Secure and Robust QR Decomposition Fragile Watermarking Scheme for Medical Images.
• Quantification of Epicardial and Thoracic Adipose Tissue using Krill Herd Optimized CNN
• A Data Mining Approach Combining Fuzzy K-Means Clustering With Bagging Neural Network for Short-Term Wind Power Forecasting.
• Heterogeneous Ensemble Classifier Model for Early Alzheimer’s Disease Diagnosis.
• Thermal Imaging Based Evaluation of Seed.
• An Efficient Approach for Facial Recognition based on AAM and CNN.
• Performance Comparison of Image Retrieval System Using Local Binary pattern in Wang database with various Distance measures.
• An Efficient Segmentation of Cervical Cells using RFC.
• ELM Based Classification of Retinal Lesion Detection Using Dynamic Shape features Segmentation.