2017/12/15 by Egor Ershov, Ershov, E. I., Simon Karpenko +1 · 1 citation
Computer Science · Engineering · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image Processing and 3D Reconstruction #Image and Object Detection Techniques #Robotics and Sensor-Based Localization
paper · pdf · doi:10.48550/arxiv.1712.05615
openalex publication_date 2017/12/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Hough transform is a popular low-level computer vision algorithm. Its computationally effective modification, Fast Hough transform (FHT), makes use of special subsets of image matrix to approximate geometric lines on it. Because of their special structure, these subset are called dyadic patterns. In this paper various properties of dyadic patterns are investigated. Exact upper bounds on approximation error are derived. In a simplest case, this error proves to be equal to (1)/(6) log(n) for n × n sized images, as was conjectured previously by Goetz et al.