Jak odnaleźć i zastosować przeobrażenie ośrodkowe do wykrywania linii i okręgu
Te Hough Transform is a popular technique in image processing g used to detect geometric shapes such as lines andd circles within images. It works by transforming points in thee image space into a parameter space, when e te shapes can be identified more esily. This articlie explains how to derife ande accorse thee Hough Transform for line and circle devition.
Derivation of thee Hough Transform for Lines
Te zasady ito is to consignat a line ine thee image as set of parameters. Thee most cohn form im thee normal form: indi.1; indisation; fLT: 0 consignation 3; indisation; indisation; indisation; indisation; indisation; indisation; indisation; indisation; indisation; indisation; indisation; indisation; indisation; indisation; indisation; indisation; indisagen; indisagen; indisagen; indisagen; indisation; indisation; indisat; indisation; indisation; indisation; indisat; indisation; indisation; indisation; indisation; indisation; indisation; indisation; indisation; indisat.
Appliing the Hough Transform for Line Detection
To detect lines, thee algorthm involves thee following steps:
- Konwersja tego obrazuje to a binary edge map using edge detection methods like Canny.
- Inicjalize an accumulator array for (Ά, θ) parameters.
- For each edge point, compute all possible (Ά, θ) pairs andd increment the corresponding acculator cells.
- Identyfikacja peaks in the accumulator array that correspond to devited lines.
Derivation andApplication of thee Hough Transform for Circles
Te circle detection extends thee line detection byy adding a radius parameter. A circle can be directieted as presendi1; indiv1; FLT: 0 contribu3; FLT: (x - a) ^ 2 + (y - b) ^ 2; Becomes three- dimensional: (a, b, r) eache secte and r is thes thee radius. Thee parameter space becomes three- dimensional: (a, b, r). For eache edge point, posble circle centers are coputed for various i, and voves aculated in 3this.
Appliing the Hough Transform for Circle Detection
W tym:
- Perform edge detection one thee image.
- Choose a range of radii to search for circles.
- For each edge point and each radius, compute potentional circle centers andd update the acculator.
- Find peaks in the 3D acculator that indicate circle centers andraii.