Thomas R. Grieve

Papers

Total Citations

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About

Thomas R. Grieve is a researcher whose work sits at the intersection of computer vision and biomedical engineering, with a particular focus on non-invasive biometric identification and medical image analysis. His most notable contribution, "Fingernail image registration using Active Appearance Models" (2013), has garnered 13 citations and demonstrates an innovative approach to biometric recognition by applying Active Appearance Models (AAM) to fingernail patterns. This work introduces a novel method for registering fingernail images using two distinct contours—one tracing the nail edge and another outlining the finger boundary—to create a robust shape model. Grieve's research addresses the growing need for reliable, non-contact biometric systems, offering potential applications in security, healthcare, and personal identification. His work stands out for its creative application of established computer vision techniques to an unconventional biometric modality, paving the way for further exploration of fingernail-based recognition systems. By bridging the gap between theoretical modeling and practical implementation, Grieve has contributed valuable insights to the fields of image registration and biometrics, making his research a useful reference for students and professionals interested in alternative identification methods.