A. Ben Hamza received his Ph.D. degree in Electrical Engineering from North Carolina State University in 2003, where he worked on computational imaging, 3D object recognition, and information theory. Prior to joining Concordia University, he was a postdoctoral research associate at Duke University, affiliated with both the Department of Electrical and Computer Engineering and the Fitzpatrick Center for Photonics and Communications Systems. He is a licensed Professional Engineer (P.Eng.) registered in Ontario, and a Senior Member of the IEEE.

His current research interests include multivariate statistical quality control, 3D computer graphics, multimedia security, and multisensor data processing.

Software Quality Assurance: Defect Prediction Modeling

Software defects entail a highly-significant cost penalty in lost productivity and post-release maintenance. Early defect prevention and removal techniques can substantially enhance the profit realized on software products. The motivation for software quality improvement is most often expressed in terms of increased customer satisfaction with higher product quality. Thus, knowledge about how many defects to expect in a software product at any given stage during its development process is a very valuable asset. The great challenge, however, is to devise efficient and reliable prediction models for software defects.

Y. Luo, T. Bergander, A. Ben Hamza "Software reliability growth modelling using a weighted Laplace test statistic,'' Proc. IEEE International Computer Software and Applications Conference, Beijing, China, 2007.

T. Bergander, Y. Luo, A. Ben Hamza "Software defects prediction using operating characteristic curves,'' Proc. IEEE International Workshop on Software Stability at Work, Las Vegas, USA, 2007.

Geometric and Topological Modeling of 3D Graphics

In recent years there has been an increasing interest in recognition of 3D shapes. Its importance is also increasing rapidly in the field of computer graphics and multimedia communication because it is difficult to process information efficiently without its recognition. 3D objects consist of geometric and topological information, and their compact representation is an important step towards a variety of computer vision applications including indexing, retrieval, and matching in a database of 3D models.

A. Ben Hamza, Hamid Krim "Geodesic matching of triangulated surfaces," IEEE Transactions on Image Processing, vol. 15, no. 8, pp. 2249- 2258, August 2006.

Biometric Classification using Pyroelectric Sensors

Biometric systems are widely used in person verification and secure identification. Unique identification is a gateway to many technologies, particularly user-based services that are very local in nature, such as access control to secure locations. Human tracking systems are mainly interested in determining the existence and location of humans within regions of open space. A tracking sensor and a biometric sensor perform a similar measurements, modulating their output based on the activity of the human within their fields of view.

John Burchett, M. Shankar, A. Ben Hamza, B.D. Guenther, N. Pitsianis, David J. Brady "Lightweight biometric detection system for human classification using pyroelectric infrared detectors," Applied Optics, vol. 45, no. 13, pp. 3031-3037, May 2006.

Multimedia Security and 3D Watermarking

The recent growth of networked multimedia systems has increased the need for multimedia security. This is very important for the protection of intellectual property rights. Copyright protection involves the authentication of digital material ownership, and the identification of illegal copies of all media: images, music, video, and 3D graphics. Digital watermarking is a key process for the protection of copyright ownership of electronic data. It creates a digital identity for all media content, provides a solution to illegal copying of digital material, and has a growing number of applications including authentication of multimedia content, certification, broadcast & internet monitoring, forensic tracking, and e-commerce.

E. Abdallah, A. Ben Hamza, P. Bhattacharya "Spectral graph-theoretic approach to 3D mesh watermarking,'' Proc. ACM Graphics Interface Conference, Montreal, Canada, 2007.

3D Mesh Quality Improvement

The great challenge in image processing and computer graphics is to devise computationally efficient and optimal algorithms for recovering images and 3D models contaminated by noise and preserving their geometrical structure. With the increasing use of scanners to create 3D models which are usually represented as triangle meshes, there is a rising need for robust and efficient 3D mesh denoising techniques to remove undesirable noise from the data.

Ying Zhang, A. Ben Hamza "Vertex-based diffusion for 3D mesh denoising," IEEE Transactions on Image Processing, vol. 16, no. 4, pp. 1036-1045, April 2007.

Multisensor Data Processing

Multisensor data fusion technology combines data and information from multiple sensors to achieve improved accuracies and better inference about the environment that could be achieved by the use of a single sensor alone. The goal of georegistration is to align a target DEM to the geographic location of a reference DEM using global or feature-based techniques. Our proposed method falls into the category of feature-based techniques which require that features be extracted and described before two DEMs can be registered.