1. Current Trends in Image Processing ResearchBy
Dr. G. R. Sinha
Senior Grade IEEE Member
Professor (Electronics & Tele. ) & Associate Director
Faculty of Engineering & Technology
Shri Shankaracharya Technical Campus, Bhilai, INDIA

2. Outline of Talk!!! Introduction Current Trends
Implementation and Challenges
Scope of Research
Privacy and Security Issues
Current Trends in DIP Research Dr G R Sinha th November 2013

3. Introduction
In last decade, there has been numerous research contributions in the field of digital image processing. Some of the major areas of application are:
Biometrics
Medical Imaging
Remote Sensing and Satellite Imaging
Surveillance
CBIR
Current Trends in DIP Research Dr G R Sinha th November 2013

4. New Challenges
It is expected to have an impact on robotics, medicine, surveillance, virtual reality, metrology, and human–computer interfaces.
More emphasis on human perception, acquisition and display devices.
Models of human perception, different imaging modalities, compressive sensing, imaging and video networks, scene analysis, biomedical and biological image processing.
Current Trends in DIP Research Dr G R Sinha th November 2013

5. Image Registration
Image registration is a process of matching and overlaying two or more images of the same scene.
It is one of the most important image processing operations in medical imaging, remote sensing, surveillance, robot vision, quality inspection etc.
This is a necessary step when performing image fusion and detecting changes.
Current Trends in DIP Research Dr G R Sinha th November 2013

6. Cultural Heritage and Restoration
Art restorers and conservators use various visual sensors for better analysis of old artworks and modern image processing methods can facilitate their work.
Material Research and analysis of Microscopic Samples.
Current Trends in DIP Research Dr G R Sinha th November 2013

7. Image Forensics
Development of mathematical and computational algorithms capable of detecting the traces of tampering in digital images.
Current Trends in DIP Research Dr G R Sinha th November 2013

8. Microscopic Image Processing
Manual processing of microscopy images is very tedious and prone to errors.
Main tasks in processing are segmentation of cells from the background, segmentation of individual cells and their tracking over time.
Current Trends in DIP Research Dr G R Sinha th November 2013

9. Detection Traces
Current Trends in DIP Research Dr G R Sinha th November 2013

10. ISL Biometrics
Current Trends in DIP Research Dr G R Sinha th November 2013

11. Challenges in Biometrics
Large intra-class variability
Noisy and distorted images
System performance (error rate, speed etc.)
Attacks on the biometric system
Every biometric characteristic has some limitations
Current Trends in DIP Research Dr G R Sinha th November 2013

12. Imperfect Images
Current Trends in DIP Research Dr G R Sinha th November 2013

13. Vulnerabilities Override Final Decision Y/N Stored Templates
Modify Template
Override Feature Extractor
Intercept the channel
Sensor
Feature
Extractor
Matcher
Y/N
Application Device
Synthesized
Feature Vector
Override Final Decision
Replay Old Data
Fake Biometric
Override Matcher
Current Trends in DIP Research Dr G R Sinha th November 2013

14. Multimodal Biometrics
Multimodal biometrics improves performance
A combination of uncorrelated modalities (e.g. fingerprint, iris and face etc.) is expected to result in improvement in performance than a combination of correlated modalities.
Current Trends in DIP Research Dr G R Sinha th November 2013

15. Feature Level Score Level Decision Level
Current Trends in DIP Research Dr G R Sinha th November 2013

16. Architecture of Multimodal Biometrics
Current Trends in DIP Research Dr G R Sinha th November 2013

17. Fusion
Current Trends in DIP Research Dr G R Sinha th November 2013

18. contd..
Current Trends in DIP Research Dr G R Sinha th November 2013

19. Major Challenges Big Data Retrieval Time Poor resolution of image
Blurring due to motion
Poor focusing and lighting
Improper scanning or interlacing
Awareness
Current Trends in DIP Research Dr G R Sinha th November 2013

20. Parallel Image Processing may help
Client
Server
Communication medium
Node-1
Node-2
Node-3
Node-4
Node-5
Node-6
Fractal Image Compressor
Parallel Fractal Image Compression
Input Image
Image De-compressor
Decompressed Image
Fractal image Decompression
Current Trends in DIP Research Dr G R Sinha th November 2013

21. Soft computing tools help to great extent
Computers are used to emulate the reasoning, problem-solving, creativity, and planning behaviors of human beings so that they can solve problems that are too large or too complex to be solved with traditional techniques.
The tools are:
Fuzzy Sets
Neuron Networks
Expert Systems (Knowledge-Based Systems)
Genetic Algorithms
Current Trends in DIP Research Dr G R Sinha th November 2013

22. Privacy Issues
The biometric systems require personal data and therefore the issues related to personal privacy of an individual are of concern.
The issues related to attitude of people and willingness to use biometric technologies are important factors in their design and implementation.
Biometric systems have to ensure that there is no infringement or invasion of privacy of the people concerned. Their personal entities are stored as digital data for verification and the data is safeguarded.
Current Trends in DIP Research Dr G R Sinha th November 2013

23. Soft Biometrics
Soft biometrics uses characteristics of people such as scars, marks, tattoos, color of eye and hair color, etc., which provide some information about the individual.
These traits may be acquired and stored along with the primary data during the enrollment stage.
Utilization of micro-level facial marks, moles, scars, etc., can help in achieving performance improvement in facial biometrics.
Scars, marks and tattoos are employed by law enforcement agencies for identification of suspects.
Current Trends in DIP Research Dr G R Sinha th November 2013

24. Advantages of Soft Biometrics
Soft biometric traits are as significant for each individual as they are distinctive.
Most people carry soft biometric features in some form.
The soft biometric features can never be transferred to another person.
False derivations from these characteristics are very difficult as the template cannot be tampered with unlike in conventional biometrics.
Current Trends in DIP Research Dr G R Sinha th November 2013

25. Disadvantages
These features used in soft biometrics cannot be solely relied upon for large scale implementations such as AADHAAR as the color of eyes and hair can be changed at will.
The feature extraction methods presently used are not sufficient for soft biometrics.
Current Trends in DIP Research Dr G R Sinha th November 2013

26. Innovative & Inspiring Equation
E =mc2 m = Motivation c = Commitment E = Excellence
Current Trends in DIP Research Dr G R Sinha th November 2013

27. Thank You
for
Kind Attention
Any Queries Please!!