2017 Fourth International Conference on Image Information Processing (ICIIP-2017) , December  21 - 23, 2017
IEEE Conference Record Number #41247

2017 Fourth International Conference
Image Information Processing
(ICIIP -2017)
December    21 - 23, 2017
Jaypee University of Information Technology
Waknaghat, District Solan, Near Shimla, Himachal Pradesh, INDIA

Special Sessions

Chair: Dr. Shriram K Vasudevan,
Amrita Vishwa Vidyapeetham (University), Coimbatore, India

Image Processing for Human Computer Interaction
In this Internet era, almost everyone is interacting with digital gadgets such as Computers, mobiles etc. in one way or the other. These gadgets have become a necessity than just a need. With the rapid increase in the usage of computers, the way of interaction between humans and machines provides an area of interest for researchers. This geared up and catalyzed the research and led to the development of the massive field - Human Computer Interaction or Man-Machine Interaction. HCI aims at building interactive computing systems to facilitate the communication between humans and computer.  Augmented Reality and Virtual Reality have become the most wanted area in research. Image processing is a major component in both AR and VR applications. The session is aimed at inviting papers which involve image processing techniques for AR and VR application developments.
Topics and Areas of Interest
Human Computer Interaction, Augmented Reality, Virtual Reality, Image Processing for AR, Image depth, Gesture
Dr. Shriram K Vasudevan
Assistant Professor (Sel.Grade) 
Dept. of Computer Science and Engineering
Amrita School of Engineering 
Amrita Vishwa Vidyapeetham (University) 
Coimbatore, India. 
Mail: kv_shriram@cb.amrita.edu and shriramkv@gmail.com

Chair: Dr. Debabala Swain,
KIIT University, Bhubaneswar, India

Smart Image Security in Digital Life
In the present day scenario the cloud computing exhibits, remarkable potential to provide cost effective, easy to manage, elastic, and powerful resources on the fly, over the Internet with optimal and shared resource utilization. IoT consist of billions of digital devices, people, services and other physical objects having the potential to seamlessly connect, interact and exchange information about themselves and their environment. It makes our lives simpler through a digital environment that will be sensitive, adaptive, and responsive to human needs. The above mentioned features encourage the organizations and individual users to shift their applications and services to the cloud through IOT. Providing greater insight and control over elements in our increasingly connected lives, the Internet of Things (IoT) emerges at a time when threats to our data and systems have never been greater. There is an average of thirteen enterprise security breaches every day, resulting in roughly 10 million records lost a day or 420,000 every hour. With the increasing importance of multimedia in people's daily life, especially images taking huge part in digital communication. Image security rises as a vital challenge for researchers in IOT and cloud computing environment.
Topics and Areas of Interest

  • Image Security Threats In Cloud
  • Image  Management In Cloud
  • Image Filtration In Cloud
  • Unethical Image Tracking In Cloud
  • Distorted Image Maintenance In Cloud
  • Image Security Through Smart Cloud Devices
  • Privacy Issues In Medical Image Sharing In Cloud
  • Fusion Image Recovery In Cloud
  • Access control and image authentication in IoT
  • Know your enemy in IoT
  • Image security breach in IoT 
  • Security installation in IoT devices
  • Image security in Robotic systems
  • Image security in Real time systems

Dr Debabala Swain
Assistant Professor(Sr Grade),
School of Computer Engineering
KIIT University, Bhubaneswar, Odisha-751024
Email: debabala.swain@gmail.com, debabala.swainfcs@kiit.ac.in


Chair: Er. RMD. Sundaram,
Wipro Technologies, Bengaluru, India

Intricacies in Image steganography and Innovative Directions
With the advancement in digital communication and data sets getting huge due to computerization of data gathering worldwide, the need for data security in transmission also increases. Cryptography and steganography are well known methods available to provide security where the former use techniques that control information in order to cipher or hide their presence and the latter concentrates on data concealment. Steganography is the practice of masking data especially multimedia data within another data. Visual contents gets more importance from people compared to audio contents and moreover visual content file is huge when compared to audio file thereby helping increase robustness of the hiding algorithms. The session is aimed at inviting papers which involve image steganography, the complexities involved in the same along with the possible solutions..
Topics and Areas of Interest
Steganography, Data hiding, Transformed domain processing, Data encryption Standard, Image depth, XOR Manipulations
Er. RMD. Sundaram
Software Architect 
Product Engineering Services Division
Wipro Technologies
Bengaluru, India
Mail: sundaram.ramanathan@wipro.comand rmdsundaram@yahoo.com


Chair: Dr G R Sinha, ,
CMR Technical Campus Hyderabad, India

Deep Learning in Biometrics
Biometrics being a popular research area, the quantum of research work in conventional biometrics is huge. Biometrics can be implemented with broader research objective and impact of large scale projects such as AADHAAR implementation of Government of India that empowers every citizen of its country with unique identity using multimodal biometric techniques. Biometrics uses multidisciplinary areas namely design of sensor; image processing, machine learning, computer vision, data fusion etc. There have been several advancements in these areas but some challenges still remain unaddressed completely. Training of biometric data from thousands of data and very large scale implementation are few important challenges that need attention of current research on biometrics.
Traditional biometrics may be implemented using untraditional approaches; one such untraditional approach is Deep Learning which is most emerging area currently. Feature extraction is an important task in all biometric methods since these methods operate on matching features of biometric trait. The features are trained using suitable soft computing technique such as neural network that have a number of hidden layers, one input layer and an output layer. The neurons of the network are trained using suitable learning method.  Convolutional Neural Network (CNN) is one such model of Deep Learning for face recognition overcoming the challenges thereof. CNNs are both fully and locally connected to hidden layers unlike traditional neural network because for all fully connected networks, the operation becomes computationally intensive. CNNs use parameter sharing, pooling and dropout also which reduce the number of common features to large extent and hence addressing the computational issues. When CNNs are tested for large data set which is actually the requirement in classification based applications the more computation is required.
The objective of this special session “Deep Learning in Biometrics” is to identify the challenges in biometrics; address the challenges using Deep learning; and have brainstorming deliberations on future research directions.
Topics and Areas of Interest
Deep Learning, Convolutional Neural Network, Biometrics
Dr G R Sinha,
Professor in Department of Electronics and Communication Engineering,
CMR Technical Campus Hyderabad, India
Email: drgrsinha@ieee.org