My research interests are applications of solutions to image processing problems using discrete mathematics. My current research interest is in the area of forensic steganalysis, developing a standardized steganalysis dataset. Steganalysis is the study of detecting hidden messages inside a photo, and is often based on statistics. It has been shown that the dataset used for performance evaluation of steganalysis algorithms can have a marked impact on the detection error rate. We are developing a dataset for steganalysis that is standardized and will allow the steganalysis community to devise experiments that measure algorithm performance using a statistical framework.
Past research interests have included the use of image algebra, genetic algorithms, artificial neural networks, stochastic processes, and optimization algorithms in areas such as image texture modeling for synthesis and classification; and image analysis - boundary detection, object recognition, and creating steganalysis feature sets. My work is multidisciplinary and covers a broad range of topics from computer science, electrical engineering, mathematics, statistics, and machine learning techniques.
I have taught many courses in mathematics, signal processing, image processing, digital image forensics, and related areas.