Kathryn Leonard

California State University, Channel Islands, Occidental College

Papers

Total Citations

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About

Kathryn Leonard is a researcher whose work bridges geometry, perception, and applied computer vision. Her primary research areas include shape analysis, geometric modeling, and the development of algorithms that mimic human visual understanding. A major contribution is her work on the Blum medial axis, a powerful tool for representing shape that she has applied to practical problems. In her 2013 paper, "Minimal Geometric Representation and Strawberry Stem Detection," Leonard took a crucial step toward an automated strawberry harvester by designing an algorithm that uses the medial axis to locate a berry's stem from a single image, requiring only minimal geometric information. This work demonstrates her ability to translate abstract mathematical concepts into real-world agricultural solutions. More recently, in 2022, she explored how humans perceive shape complexity in "Perceptually grounded quantification of 2D shape complexity," laying groundwork for more intuitive shape descriptors. With over 5 citations on her most-cited paper, Leonard's impact lies in her unique fusion of pure geometry with perceptual and applied challenges, making her a notable figure in shape-based computer vision and geometric computing.