Marie E. Maddix

Papers

Total Citations

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About

Marie E. Maddix’s research focuses on real-time image processing and embedded systems, with a particular emphasis on edge detection for computer and machine vision. Her major contributions lie in the practical implementation of edge detection algorithms on digital signal processors (DSPs), bridging the gap between theoretical computer vision and real-world hardware constraints. Her most cited work, “Real-time edge detection using TMS320C6711 DSP” (2004, 9 citations), demonstrates a real-time implementation of the Canny algorithm on a DSP platform, showcasing how critical edge information can be extracted from grayscale images for applications like assembly line inspection and surveillance. In a related study, “Edge detection: wavelets versus conventional methods on DSP processors” (2005, 4 citations), she compared wavelet-based approaches, notably the Haar wavelet, with traditional methods, highlighting the trade-offs in performance and accuracy for real-time systems. While her citation counts are modest, Maddix’s work is notable for its hands-on, engineering-focused approach to vision systems, making her contributions valuable for students and researchers interested in embedded vision, hardware acceleration, and the practical deployment of image processing algorithms in resource-constrained environments.