Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Zernike moment-based image analysis and its application
Pattern Recognition Letters
Shape Analysis and Classification: Theory and Practice
Shape Analysis and Classification: Theory and Practice
Digital Image Processing
Multiscale Fractal Characterization of Three-Dimensional Gene Expression Data
SIBGRAPI '02 Proceedings of the 15th Brazilian Symposium on Computer Graphics and Image Processing
A New Approach to Estimate Fractal Dimension of Texture Images
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
Matching shapes with self-intersections: application to leaf classification
IEEE Transactions on Image Processing
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The great biodiversity of species makes the plants classification a very complex and time-consuming task. The leaf is an important characteristic of the plant and it is present independently of season or plant maturity. The most relevant information about the leaf relies on shape. Its study enables us to discriminate a large set of species and to speed up the measures extraction process, which is traditionally performed manually. This paper presents a novel approach to leaf shape identification based on curvature complexity analysis. By using the Curvature Scale Space (CSS), a curve describing the complexity of the shape is achieved. Descriptors computed from this curve are used to classify a set of leaves shapes. Results demonstrate the potential of the technique, which overcome traditional shape analysis methods found in literature.