LineSegmentDetectorDetect Method (InputArray, OutputArray, OutputArray, OutputArray, OutputArray)
|
Finds lines in the input image.
This is the output of the default parameters of the algorithm on the above shown image.
Namespace:
OpenCvSharp
Assembly:
OpenCvSharp (in OpenCvSharp.dll) Version: 3.4.1.20180605-33-CaRLSharp
Syntaxpublic virtual void Detect(
InputArray image,
OutputArray lines,
OutputArray width = null,
OutputArray prec = null,
OutputArray nfa = null
)
Public Overridable Sub Detect (
image As InputArray,
lines As OutputArray,
Optional width As OutputArray = Nothing,
Optional prec As OutputArray = Nothing,
Optional nfa As OutputArray = Nothing
)
public:
virtual void Detect(
InputArray^ image,
OutputArray^ lines,
OutputArray^ width = nullptr,
OutputArray^ prec = nullptr,
OutputArray^ nfa = nullptr
)
abstract Detect :
image : InputArray *
lines : OutputArray *
?width : OutputArray *
?prec : OutputArray *
?nfa : OutputArray
(* Defaults:
let _width = defaultArg width null
let _prec = defaultArg prec null
let _nfa = defaultArg nfa null
*)
-> unit
override Detect :
image : InputArray *
lines : OutputArray *
?width : OutputArray *
?prec : OutputArray *
?nfa : OutputArray
(* Defaults:
let _width = defaultArg width null
let _prec = defaultArg prec null
let _nfa = defaultArg nfa null
*)
-> unit
function Detect(image, lines, width, prec, nfa);
Parameters
- image
- Type: OpenCvSharpInputArray
A grayscale (CV_8UC1) input image. - lines
- Type: OpenCvSharpOutputArray
A vector of Vec4i or Vec4f elements specifying the beginning and ending point of a line.
Where Vec4i/Vec4f is (x1, y1, x2, y2), point 1 is the start, point 2 - end. Returned lines are strictly oriented depending on the gradient. - width (Optional)
- Type: OpenCvSharpOutputArray
Vector of widths of the regions, where the lines are found. E.g. Width of line. - prec (Optional)
- Type: OpenCvSharpOutputArray
Vector of precisions with which the lines are found. - nfa (Optional)
- Type: OpenCvSharpOutputArray
Vector containing number of false alarms in the line region,
with precision of 10%. The bigger the value, logarithmically better the detection.
See Also