Back close
Admissions
About the Lab / Centre

This lab was established in the year 2012 with the support of Cognizant Technology solutions, India. Amrita Cognizant Innovation Lab has been setup to conduct research in the areas of Computer Vision and Image Processing, Security, and Wireless Sensor Network.

Research
  • Computer Vision and Image Processing
  • Real time Object Detection and Recognition
  • Image/Video Classification
  • Video Surveillance,
  • Humanoid Robotics,
  • Vision based Robot for Navigation and Object Identification
Projects
  • An automated vision-based algorithm for out of context detection in images
  • An Automated Vision Based Change Detection Method for Planogram Compliance in Retail Stores
  • Query by Example—Retrieval of Images Using Object Segmentation and Distance Measure
  • Kernel Based Approaches for Context Based Image Annotatıon
  • Automated Tool for Assessment of Satellite Image Quality and Characteristics
  • Automatic book spine extraction and recognition for library inventory management.
  • Feature detection for color images using SURF
  • Enhanced Defogging System on Foggy Digital Color Images
  • Deep Learning of Generic Features for Vision
  • Autonomous guidance system for visually impaired in a library
  • Smart pharmacist for visually impaired
  • Object detection from cluttered image
  • Context based image annotation
  • Image registration using Differential Evolution based Algorithm

Facilities

Block Image

Robotic Kits

Lego Mind Storm and I-Robot enable users to create an affordable mobile robot platform easily.They help in understanding the fundamentals of robotics easily.

Block Image

Machine Vision system

The vision system from National Instruments is designed to acquire and process images in real time. The systems are ideal for complex, high-speed machine vision applications such as high-speed sorting, assembly verification, packaging inspection and surface inspection.

Block Image

Beagle & Leopard Board

The Beagle Board is a low-power open source hardware single-board computer produced by Texas Instruments. Leopard board is an open source hardware made as companion board for the Beagle Board.

Block Image

TP-Link IP

TP-Link IP (Wireless Day/Night Surveillance Camera, Wireless Pan/Tilt Surveillance Camera) provides students a platform to analyze and build surveillance and tracking based applications.

Block Image

GPU

Nvidia GEFORCE GT240 graphic Card and AMD Radeon™ HD 6670 Graphics card are provided to implement and test GPU based computing paradigms.

Block Image

Kinect

Kinect for Windows sensor and software development kit (SDK) offer a superior development platform for Windows with camera, infrared, depth data and accelerometer features.

Block Image

Universal Software Radio Peripheral (USRP)

for Cognitive Radio Development is a tool for rapid prototyping and deployment of software radios.

The general purpose equipment available in the lab are
  • HP Z400 workstation
  • HP 6200DX PC – 5 systems
  • LCD projector
Publications
  1. Karthika, R., and Latha Parameswaran. “An Automated Vision-based Algorithm for Out of Context Detection in Images” International Journal of Signal and Imaging Systems Engineering1 (2018): 1-8.
  2. Muthugnanambika, M., et al. “An Automated Vision Based Change Detection Method for Planogram Compliance in Retail Stores.” Computational Vision and Bio Inspired Computing. Springer, Cham, 2018. 399-411.
  3. Sathya, S., Latha Parameswaran, and R. Karthika. “Query by Example—Retrieval of Images Using Object Segmentation and Distance Measure.” Computational Vision and Bio Inspired Computing. Springer, Cham, 2018. 512-522.
  4. Nair, L. Swati, R. Manjusha, and Latha Parameswaran. “Kernel Based Approaches for Context Based Image Annotatıon.” Computational Vision and Bio Inspired Computing. Springer, Cham, 2018. 249-258.
  5. Deepak, P. Muni, et al. “Automated Tool for Assessment of Satellite Image Quality and Characteristics.” Computational Vision and Bio Inspired Computing. Springer, Cham, 2018. 663-679.
  6. Kamalaveni, V., S. Veni, and K. A. Narayanankutty. “Improved self-snake based anisotropic diffusion model for edge preserving image denoising using structure tensor.” Multimedia Tools and Applications18 (2017): 18815-18846.
  7. Vanjigounder, Kamalaveni, and Narayanankutty KA. “Performance Comparison of Total Variation based Image Regularization Algorithms.” International Journal on Advanced Science, Engineering and Information Technology4 (2016): 419-425.
  8. Venkataraman, D., and N. Mangayarkarasi. “Support vector machine based classification of medicinal plants using leaf features.” 2017 International conference on advances in computing, communications and informatics (ICACCI). IEEE, 2017.
  9. Venkataraman, D., and N. Mangayarkarasi. “Computer vision based feature extraction of leaves for identification of medicinal values of plants.” 2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC). IEEE, 2016.
  10. Sarkar, Ankita, and S. Padmavathi. “Image pyramid for automatic segmentation of fabric defects.” Computational Vision and Bio Inspired Computing. Springer, Cham, 2018. 569-578.
  11. Krishnan, Sarath, et al. “Enhanced Defogging System on Foggy Digital Color Images.” Computational Vision and Bio Inspired Computing. Springer, Cham, 2018. 488-495.
  12. Sujee, R., and S. Padmavathi. “Image enhancement through pyramid histogram matching.” 2017 International Conference on Computer Communication and Informatics (ICCCI). IEEE, 2017.
  13. Nehru, Mangayarkarasi, and S. Padmavathi. “Illumination invariant faces detection using viola jones algorithm.” 2017 4th International Conference on Advanced Computing and Communication Systems (ICACCS). IEEE, 2017.
  14. Muthugnanambika, M., and S. Padmavathi. “Feature detection for color images using SURF.” 2017 4th International Conference on Advanced Computing and Communication Systems (ICACCS). IEEE, 2017.
  15. Swapna, T. R., et al. “Computational Approach for Clinically Significant Macular Edema Detection Using Fundus Fluorescein Angiogram Images.” Journal of Medical Imaging and Health Informatics8 (2017): 1689-1692.
  16. Swapna, T. R., Chandan Chakraborty, and K. A. Narayanankutty. “Correlated Analysis of Morphological Patterns Between SD-OCT and FFA Imaging for Diabetic Maculopathy Detection: Conformal Mapping-Based Approach.” Proceedings of the International Conference on Soft Computing Systems. Springer, New Delhi, 2016.
  17. Vinodhini, R. E., P. Malathi, and T. Gireesh Kumar. “A survey on DNA and image steganography.” 2017 4th International Conference on Advanced Computing and Communication Systems (ICACCS). IEEE, 2017.
  18. Malathi, Pa, et al. “Highly Improved DNA Based Steganography.” Procedia Computer Science 115 (2017): 651-659.
  19. Malathi, P., and T. Gireeshkumar. “Relating the Embedding Eficiency of LSB Steganography Techniques in Spatial and Transform Domains.” Procedia Computer Science 93 (2016): 878-885.
  20. Baskar, A., and T. Gireesh Kumar. “Facial Expression Classification Using Machine Learning Approach: A Review.” Data Engineering and Intelligent Computing. Springer, Singapore, 2018. 337-345.
  21. Nevetha, M. P., and A. Baskar. “Automatic Book Spine Extraction and Recognition for Library Inventory Management.” Proceedings of the Third International Symposium on Women in Computing and Informatics. ACM, 2015.
  22. Nevetha, M. P., and A. Baskar. “Applications of Text Detection and its Challenges: A Review.” Proceedings of the Third International Symposium on Women in Computing and Informatics. ACM, 2015.
  23. Srunitha, K., and D. Bharathi. “Mango Leaf Unhealthy Region Detection and Classification.” Computational Vision and Bio Inspired Computing. Springer, Cham, 2018. 422-436.
  24. Sathish, P., and D. Bharathi. “Automatic Road Sign Detection and Recognition Based on SIFT Feature Matching Algorithm.” Proceedings of the International Conference on Soft Computing Systems. Springer, New Delhi, 2016.
  25. Vikram, K., Hema P. Menon, and Dhanya M. Dhanalakshmy. “Segmentation of Brain Parts from MRI Image Slices Using Genetic Algorithm.” Computational Vision and Bio Inspired Computing. Springer, Cham, 2018. 457-465.
  26. Sreelakshmi, S., Anupa Vijai, and T. Senthilkumar. “Detection and Segmentation of Cluttered Objects from Texture Cluttered Scene.” Proceedings of the international conference on soft computing systems. Springer, New Delhi, 2016.

People

Baskar A.
Baskar A.

Assistant. Professor, Computer Science, School of Engineering, Coimbatore

Research
  • Information security
  • Cryptanalysis of Web
  • Networks (Wired, Wireless and Mobile)
  • Malware Analysis
Projects
  • A Secure and Efficient Location Update Scheme for Next Generation Proxy Mobile IP in Distributed Environment
  • Dual Quorum-Dispersal- A Novel Approach for Reliable and Consistent ECC based Storages
  • Enhancing the design of dual Quorum – dispersal for hybrid failures
  • Novel Multi-Factor Authentication Scheme using QR-Code
  • Self Organizing trust model for Peer to Peer systems using Genetic Algorithms
  • Analysis of twitter feeds using NLP and machine learning
  • Mozilla OS application security
  • Identifying Sybil Nodes in a Social Network
  • Attack analysis on 4G network
  • Evaluating the Effectiveness of Conventional Fixes for SQL Injection Vulnerability
  • An Analysis of Black-Box Web Application Vulnerability Scanners in SQLi Detection

Facilities

Block Image

Apple book Pro MD101HN/ MACBOOK PRO 13” DUAL CORE 15 2.5 ghZ/4 gb ram/500 gb hdd/hd graphic 4000

Block Image

i7/500GB(HP ProDesk400 G2MT)

Graphics controller AMD radeon HD 8470

Core clock 775 MHz

Memory clock 900 MHz

Memory 2GB, DDR3, 64-bit wide

Block Image

HP L3 Switch( 5500-24G EI)

4 RJ-45 autosensing 10/100/1000 ports (IEEE 802.3 Type 10BASE-T, IEEE 802.3u Type 100BASE-TX, IEEE 802.3ab Type 1000BASE-T)

Media Type: Auto-MDIX

Duplex: 10BASET/ 100BASE-TX: half or full

1000BASE-T: full only 4 dual-personality ports

auto-sensing 10/100/1000Base-T or SFP 2 port expansion module slots

Supports a maximum of 24 autosensing 10/100/1000 ports

Block Image

HP L2 Switch (5120 24G SI)

24 RJ-45 autosensing 10/100/1000 PoE+ ports (IEEE 802.3 Type 10BASE-T, IEEE 802.3u Type 100BASE-TX, IEEE 802.3ab Type 1000BASE-T, IEEE 802.3at PoE+); Duplex: 10BASE-T/100BASE-TX: half or full; 1000BASE-T: full only 4 fixed Gigabit Ethernet SFP ports

Block Image

Hikvision IP Camera (DS2DE7184A)

Image Sensor 1/2.8’P’rogressive Scan CMOS E­ective Pixel 2230K pixels Min. Illumination Color: 0.05Lux@F1.6; B/W: 0.01Lux@F1.6; 0 Lux with IR White Balance Auto / Manual /ATW/Indoor/Outdoor/Daylight lamp/Sodium lamp AGC Auto / Manual S / N Ratio ≥ 50dB Digital Noise Reduction 3D DNR Backlight Compensation BLC/DWDR Wide Dynamic Range 128X Digital WDR Shutter Speed 1 ~ 1/10,000s Day & Night IR Cut Filter Digital Zoom 16X Focus Mode Auto / Semiautomatic / Manual

Block Image

NVR(DS7604NI)

Recording Mode: Real Time / Timelapse / Event

Video inputs: 4

Block Image

iball Camera CHD20

USB Interface USB 2.0, backward compatible with USB 1.1

Microphone Bult-in USB

Focus Manual Focus

Maximum Image Resolution 5500 x 3640 Pixels

Block Image

MOTO E Android Device

Processor 1.2GHz dual-core

Processor make Qualcomm Snapdragon 200

RAM 1GB

Internal storage 4GB

Expandable storage Yes

Expandable storage type microSD

Expandable storage up to (GB) 32

Operating system Android 4.4

Connectivity Wifi Yes

Publications

People

Dr. Harini N.
Dr. Harini N.

Assistant. Professor, Computer Science, School of Engineering, Coimbatore

Projects
  • Trust based Solution for Ad-hoc Networks
  • Energy Efficient Mobility Prediction Based Localization Algorithm for Mobile Sensor Networks
  • Design of fault tolerant wireless sensor Network with mobile sink
  • Structural health monitoring using WSN and study of the performance.
  • Algorithms for Localization and clustering in wireless sensor networks, and studying their performance in terms of energy efficiency and network lifetime.
  • Deriving shortest path algorithm to perform efficient routing in wireless sensor networks
  • Deriving solutions for coverage issues in WSN environment.
  • Optimization algorithm for WSN environment ( in terms of routing, localization and coverage)
  • Security Algorithms for WSN environment’s to protect the system from intruders( includes data and network security)
  • Applying machine learning algorithms to perform efficient routing in WSN environment and study of their performances.
  • Establishing communication across heterogeneous networks, solving the interoperability issues.
  • Real-time testbed design of sensors for smart farming.
Lab Equipments
Raspberry Pi 3 Model B+ Complete Kit
Arduino Mega
Zigbee Module
Low Energy Bluetooth 4.0 Module-DBM01
GSM & GPRS Module SIM 800
iTead Soil Moisture Sensor
Sonoff TH10
WASP MOTE (starter kit)
thingBot-LoRa
thingBot-ESP
thingBot-15.4
Long Range Wireless Modules(595-LAUNCHXL-CC1310)
Wi-Fi modules(595-CC3200-LAUNCHXL)
Solinoid valve
Beaglebone Black Wireless
GPS Receiver with Antenna -RS232 Serial
SIM808 GSM/GPRS/GPS UART Mini Modem
Lab Equipments Available in the Lab
Sl. No Component
1 Raspberry Pi 3 Model B+ Complete Kit
2 Bread board
3 Wireless routers and modems
4 IR Object Sensor
5 Arduino Mega
6 Zigbee Module
7 Bluetooth Module
8 GSM & GPS module
9 Soil / Dust / Humidity / Water / Moisture Sensor
10 iTead soil moisture sensor
11 UltraSonic Distance Sensor Module
12 Ambient Humidity Module (digital)
13 Sonoff TH10
14 WASP MOTE (starter kit)
15 AC-DC converter (5V/3.3V output)
16 thingBot-LoRa
17 thingBot-Base
18 LoRa-GW
19 Arduino LoRa Shield
20 Arduino GSM Shield
21 temperature sensor probes – NTC
22 ePro Labs SEN-0021 Pir Sensor Hc-Sr501 Motion Sensor
23 thingBot-ESP
24 Witooth
25 BLE Beacon
26 thingBot-15.4
27 Cables, Connectors ,HDMI cable, D-type connectors,USBmicro,SD card for rasberry pie,power bank,USB
28 Xb shield +Xb +arduino
29 Long Range Wireless Modules(595-LAUNCHXL-CC1310)
30 Wi-Fi modules(595-CC3200-LAUNCHXL)
31 Soild State Relay with PCB(solid state relay)
33 Jumper Wires, female to female jumper wires
34 Water / Rainfall Sensor
35 AC current sensor 100A
36 Soil / Dust / Humidity / Water / Moisture Sensor
37 Water Flow Sensor
38 temperature controlled soldering device
39 Solinoid valve
40 Beaglebone black wireless
41 beaglebone cover
Lab Equipment’s (For Which Order is Placed)
Sl. No Component
1 Grove Multichannel Gas Sensor
2 Grove Electricity Sensor
3 Grove Flame Sensor
4 Grove Dust Sensor
5 Grove Air Quality Sensor
6 DHT22 Temperature – Humidity Sensor Module
7 Raspberry Pi Sense HAT – For the Pi 3 / 2 / B+ / A+
8  USB A-microB Cable
9 NodeMCU v2 – Lora Based ESP8266 Development Kit
10 5MP Camera for Raspberry Pi with Night Vision
11 7 Inch Touch Screen LCD for Raspberry Pi with Bicolor Case
12 Raspberry Pi 3 B+ Official Casing
13 D00162 –  Screwdriver Kit, Phillips, Torx, Hex, Slotted, Assorted Accessories, 42 Pieces
14 Hole pcb
15 Keyboard and Mouse
16 Jumper Wire
17 Digital Multimeter(V92A)
18 Breadboard
19 37 in 1 Sensor Modules Kit for Arduino Uno, Mega 2560, Raspberry Pi
20 5v 2A USB Adaptor
21 Sensor Kit
22 Resistor Kit
23 Capacitor Kit
24 Led Kit
25 Mosfet
26 Generic Electronic Kit
27 Header Pin Female
28 Header Pin Male
29 Header Pin L
Publications
Patents

Received an Indian patent on Multi Secured Dropping of Spoofed Packets at the Gateway for Unauthorized Networks, Grantee: Sridharan Krishnan, Loganathan Vinoth and Dr.N.Radhika in the year 2019.

People

Dr. Radhika N.
Dr. Radhika N.

Professor, Computer Science, School of Engineering, Coimbatore

Admissions Apply Now