Dae Hwan Hwang

Electronics and Telecommunications Research Institute

Papers

Total Citations

H-Index

About

Dae Hwan Hwang is a researcher whose work centers on advancing face recognition technology, with a particular focus on improving the accuracy and reliability of face detection and registration. His most-cited paper, "Face image registration methods using Normalized Cross Correlation" (2008, 7 citations), addresses a critical bottleneck in face recognition systems: the precise alignment of detected faces. While many systems rely on the popular Viola-Jones face detector, Hwang identified that the detected images often suffer from misalignment, degrading recognition performance. His contribution lies in developing robust registration methods using Normalized Cross Correlation to correct these errors, enhancing the overall system's effectiveness. Though his citation count is modest, his work is notable for tackling a practical, real-world challenge in biometrics—a field where even small improvements in preprocessing can have significant downstream impacts. Hwang’s research underscores the importance of meticulous image processing in building reliable face recognition systems, making his contributions valuable for students and engineers seeking to understand the nuances of face alignment and its role in successful recognition pipelines.