Shape analysis using fractal dimension: a curvature based approach
This work addresses shape analysis for computer vision applications, but it appears incremental as it builds on existing fractal and curvature techniques.
The authors tackled shape analysis by developing a novel fractal dimension method using curvature scale-space and multiscale transforms to extract precise descriptors, which were validated in classification with high reliability.
The present work shows a novel fractal dimension method for shape analysis. The proposed technique extracts descriptors from the shape by applying a multiscale approach to the calculus of the fractal dimension of that shape. The fractal dimension is obtained by the application of the curvature scale-space technique to the original shape. Through the application of a multiscale transform to the dimension calculus, it is obtained a set of numbers (descriptors) capable of describing with a high precision the shape in analysis. The obtained descriptors are validated in a classification process. The results demonstrate that the novel technique provides descriptors highly reliable, confirming the precision of the proposed method.