Digital Image Forensics: Forgery and spoofing detection

• Grant number: 08/08681-9
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Effective date (Start): April 01, 2009
• Effective date (End): December 31, 2009
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Siome Klein Goldenstein
• Grantee: Anderson de Rezende Rocha
• Host Institution: Instituto de Computação (IC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

Image tampering detection is paramount nowadays. Digital image forensics encompasses the set of tools and techniques to verify authenticity and integrity of digital images with several applications in our life. For instance, we can deploy digital forensics solutions to improve the security on biometric systems such as face and fingerprint recognition where an attacker may want to have unauthorized access to the system pretending to be someone else. The financial system is not safe either. Some observers consider check frauds as one of the most increasing crimes of the 1990s. In this context, it is necessary to devise afficient and effective automatic tools to detect such forgeries. Particularly, we are interested in designing solutions for such problems borrowing ideas from Machine Learning, Image Processing, and Computer Vision. We envision solutions related to check fraud detection as well as face and fingerprint spoofing detection. In addition, our work fits the main directions proposed in the thematic project FAPESP 07/52015-0 --- Approximation methods for visual computing --- and it is a joint initiative with University of Colorado at Colorado Springs, United States.

Scientific publications

(5)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

ROCHA, ANDERSON; GOLDENSTEIN, SIOME. Progressive randomization: Seeing the unseen. COMPUTER VISION AND IMAGE UNDERSTANDING, v. 114, n. 3, p. 349-362, MAR 2010. (07/52015-0, 08/08681-9, 05/58103-3)

SCHEIRER, WALTER; ROCHA, ANDERSON; MICHEALS, ROSS; BOULT, TERRANCE; DANIILIDIS, K; MARAGOS, P; PARAGIOS, N. Robust Fusion: Extreme Value Theory for Recognition Score Normalization. Lecture Notes in Computer Science, v. 6313, p. 3-pg., 2010-01-01. (08/08681-9)

SCHEIRER, WALTER J.; ROCHA, ANDERSON; HEFLIN, BRIAN; BOULT, TERRANCE E.; IEEE. Difficult Detection: A Comparison of Two Different Approaches to Eye Detection for Unconstrained Environments. 2009 IEEE 3RD INTERNATIONAL CONFERENCE ON BIOMETRICS: THEORY, APPLICATIONS AND SYSTEMS, v. N/A, p. 2-pg., 2009-01-01. (08/08681-9)

ROCHA, ANDERSON; SCHEIRER, WALTER; BOULT, TERRANCE; GOLDENSTEIN, SIOME. Vision of the Unseen: Current Trends and Challenges in Digital Image and Video Forensics. ACM COMPUTING SURVEYS, v. 43, n. 4, OCT 2011. (07/52015-0, 08/08681-9, 05/58103-3, 10/05647-4)

ROCHA, ANDERSON; HAUAGGE, DANIEL C.; WAINER, JACQUES; GOLDENSTEIN, SIOME. Automatic fruit and vegetable classification from images. COMPUTERS AND ELECTRONICS IN AGRICULTURE, v. 70, n. 1, p. 96-104, JAN 2010. (07/52015-0, 08/08681-9, 05/58103-3, 08/54443-2)