A Method of Detecting End-To-End Curves of Limited Curvature
This work addresses a specific problem in computer vision for detecting structured curves, but it appears incremental as it builds on existing dynamic programming and Hough transform techniques.
The paper tackles the problem of detecting end-to-end curves with limited curvature, such as k-link polylines, by maximizing a quality function in an image matrix using dynamic programming over Fast Hough Transform results. The method achieves an asymptotic complexity of O(h·(w + h/k)·log(h/k)), comparable to fast transforms, and is demonstrated on synthetic and real data.
In this paper we consider a method for detecting end-to-end curves of limited curvature like the k-link polylines with bending angle between adjacent segments in a given range. The approximation accuracy is achieved by maximization of the quality function in the image matrix. The method is based on a dynamic programming scheme constructed over Fast Hough Transform calculation results for image bands. The proposed method asymptotic complexity is $O(h \cdot (w+ \frac{h}{k}) \cdot log(\frac{h}{k}))$, where $h$ and $w$ are the image size, and $k$ is the approximating polyline links number, which is an analogue of the complexity of the fast Fourier transform or the fast Hough transform. We also show the results of the proposed method on synthetic and real data.