Open AccessEFFICIENT LINE DETECTION METHOD BASED ON 2D CONVOLUTION FILTER
Author(s) -
Paweł Kowalski,
Piotr Tojza
Publication year - 2021
Publication title -
informatyka, automatyka, pomiary w gospodarce i ochronie środowiska
Language(s) - English
Resource type - Journals
eISSN - 2391-6761
pISSN - 2083-0157
DOI - 10.35784/iapgos.2817
Subject(s) - convolution (computer science) , filter (signal processing) , hough transform , computation , computer science , line (geometry) , constant (computer programming) , pixel , algorithm , set (abstract data type) , scan line , computer vision , artificial intelligence , image (mathematics) , mathematics , geometry , grayscale , artificial neural network , programming language
The article proposes an efficient line detection method using a 2D convolution filter. The proposed method was compared with the Hough transform, the most popular method of straight lines detection. The developed method is suitable for local detection of straight lines with a slope from -45˚ to 45˚. Also, it can be used for curve detection which shape is approximated with the short straight sections. The new method is characterized by a constant computational cost regardless of the number of set pixels. The convolution is performed using the logical conjunction and sum operations. Moreover, design of the developed filter and the method of filtration allows for parallelization. Due to constant computation cost, the new method is suitable for implementation in the hardware structure of real-time image processing systems.