Project 1: Non-intrusive Image Forgery Detection
using Multiresolution Framework

Funding Body: KSU-KACST National Plan for Science and Technology (NPST)

Digital imaging has matured to become the dominant technology for creating, processing, and storing pictorial memory and evidence. This technology undoubtedly brings many advantages, but at the same time, it has never been so easy to manipulate images by using different powerful imaging software, often in such perfection that forgery is visually indistinguishable from authentic photographs. In view of this, the information in the form of digital images can not be unquestionable and can not be put as evidence in court and as a helping aid to security agencies. As such, image forensics has become crucial area for data security and authenticity. However, the existing non-intrusive techniques for image forensics are far from being reliable and robust. In this project, we will develop a system for reliable and robust non-intrusive forgery detection using multiresolution framework based on multiresolution framework and statistical modeling. The outcome of the project will be useful in helping the Saudi security agencies and commercial organizations such as insurance companies to establish the authenticity of pictorial information and to validate the evidence presented in the form of image data in front of court.

Duration: Two years
Responsibility: Co-Investigator with PI: Dr. Ghulam Muhammad and Co-I: Professor George Bebis and Dr. Muhammad Hussain.
Amount: 1.618 million Saudi Arabian Riyals

Project 2: Category Specific Face Recognition

Funding Body: KSU-KACST National Plan for Science and Technology (NPST)

Face recognition is a key biometric technology with a wide range of potential applications a wide range of potential applications related to security and safety including surveillance, information security, access control, identity fraud, gang tracking, banking and finding missing children. Despite considerable progress in face recognition research over the last decade, especially with the development of powerful models of appearance, today’s face recognition systems are not accurate or robust enough to be fully deployed in high security environments. Advances in this area are thus very likely to make significant contributions critical for the nation and our society in areas such as security, monitoring, surveillance, and safety. This project aspires to advance the state of art in face recognition by investigating a novel approach to face recognition using category-specific recognition. There are two key ideas behind the proposed approach: first, classifying faces into different face categories using information from various visual cues (e.g., gender, ethnicity, age, etc.); and second, designing “category specific” or “specialized” recognition processes  (e.g., Caucasian male, between 20 and 30 years old) by exploiting the most discriminatory features within each face category.

Duration: Jan 2011 ~ Dec 2012
Responsibility: Co-Investigator with PI: Dr. Muhammad
Hussain and Co-I: Professor George Bebis and Dr. Ghulam Muhammad.
Amount: 1.367 million Saudi Arabian Riyals