gusucode.com > vision工具箱matlab源码程序 > vision/+vision/en/CornerDetector.m
classdef CornerDetector< matlab.System
%CornerDetector Find corner features
% -----------------------------------------------------------------------
% The vision.CornerDetector will be removed in a future release. Use the
% detectHarrisFeatures, detectMinEigenFeatures, detectBRISKFeatures, or
% detectFastFeatures function with equivalent functionality instead.
% -----------------------------------------------------------------------
%
% The CornerDetector object finds corners in a grayscale image. It
% returns corner locations as a matrix of [x y] coordinates. The object
% provides Harris, Minimum Eigenvalue and FAST corner detectors.
%
% cornerDetector = vision.CornerDetector returns a corner detector System
% object, cornerDetector, that finds corners in an image using Harris corner
% detector.
%
% cornerDetector = vision.CornerDetector(..., 'Name', 'Value') configures
% the corner detector properties, specified as one or more name-value
% pair arguments. Unspecified properties have default values.
%
% Step method syntax:
%
% LOC = step(cornerDetector, I) finds corners in grayscale image I.
% LOC is an M-by-2 matrix of [x y] corner coordinates, where M is the
% number of detected corners. M can be less than or equal to a value
% set in MaximumCornerCount property.
%
% METRIC = step(cornerDetector, I) returns a matrix with corner metric values,
% METRIC, when the MetricMatrixOutputPort property is true. METRIC
% represents corner strength and has the same size as I.
%
% [LOC, METRIC] = step(cornerDetector, I) returns the locations of the
% corners in LOC and the corner metric matrix in METRIC, when both the
% CornerLocationOutputPort and MetricMatrixOutputPort properties are true.
%
% System objects may be called directly like a function instead of using
% the step method. For example, y = step(obj, x) and y = obj(x) are
% equivalent.
%
% CornerDetector methods:
%
% step - See above description for use of this method
% release - Allow property value and input characteristics changes
% clone - Create corner detector object with same property values
% isLocked - Locked status (logical)
%
% CornerDetector properties:
%
% Method - Method to find corner values
% Sensitivity - Sensitivity factor to detect sharp corners
% SmoothingFilterCoefficients - Coefficients of smoothing filter
% IntensityThreshold - Intensity comparison threshold
% MaximumAngleThreshold - Maximum angle in degrees to be considered
% corner
% CornerLocationOutputPort - Enables output of the corner location
% MetricMatrixOutputPort - Enables output of the metric matrix
% MaximumCornerCount - Maximum number of corners to detect
% CornerThreshold - Minimum metric value that indicates a corner
% NeighborhoodSize - Size of suppressed region around detected
% corner
%
% This System object supports fixed-point operations. For more
% information, type vision.CornerDetector.helpFixedPoint.
%
% Example
% -------
% % Detect corners in an input image.
% I = im2single(imread('circuit.tif'));
% % select FAST algorithm by Rosten & Drummond
% cornerDetector = vision.CornerDetector( ...
% 'Method', 'Local intensity comparison (Rosten & Drummond)');
%
% pts = step(cornerDetector, I);
% % note that color data range must match the data range of image I
% color = [1 0 0]; % [red, green, blue]
% % insert color marker
% J = insertMarker(I, pts, 'Color', 'red');
% imshow(J); title ('Corners detected in a grayscale image');
%
% See also detectHarrisFeatures, detectMinEigenFeatures,
% detectBRISKFeatures, detectFASTFeatures.
% Copyright 2003-2016 The MathWorks, Inc.
methods
function out=CornerDetector
%CornerDetector Find corner features
% -----------------------------------------------------------------------
% The vision.CornerDetector will be removed in a future release. Use the
% detectHarrisFeatures, detectMinEigenFeatures, detectBRISKFeatures, or
% detectFastFeatures function with equivalent functionality instead.
% -----------------------------------------------------------------------
%
% The CornerDetector object finds corners in a grayscale image. It
% returns corner locations as a matrix of [x y] coordinates. The object
% provides Harris, Minimum Eigenvalue and FAST corner detectors.
%
% cornerDetector = vision.CornerDetector returns a corner detector System
% object, cornerDetector, that finds corners in an image using Harris corner
% detector.
%
% cornerDetector = vision.CornerDetector(..., 'Name', 'Value') configures
% the corner detector properties, specified as one or more name-value
% pair arguments. Unspecified properties have default values.
%
% Step method syntax:
%
% LOC = step(cornerDetector, I) finds corners in grayscale image I.
% LOC is an M-by-2 matrix of [x y] corner coordinates, where M is the
% number of detected corners. M can be less than or equal to a value
% set in MaximumCornerCount property.
%
% METRIC = step(cornerDetector, I) returns a matrix with corner metric values,
% METRIC, when the MetricMatrixOutputPort property is true. METRIC
% represents corner strength and has the same size as I.
%
% [LOC, METRIC] = step(cornerDetector, I) returns the locations of the
% corners in LOC and the corner metric matrix in METRIC, when both the
% CornerLocationOutputPort and MetricMatrixOutputPort properties are true.
%
% System objects may be called directly like a function instead of using
% the step method. For example, y = step(obj, x) and y = obj(x) are
% equivalent.
%
% CornerDetector methods:
%
% step - See above description for use of this method
% release - Allow property value and input characteristics changes
% clone - Create corner detector object with same property values
% isLocked - Locked status (logical)
%
% CornerDetector properties:
%
% Method - Method to find corner values
% Sensitivity - Sensitivity factor to detect sharp corners
% SmoothingFilterCoefficients - Coefficients of smoothing filter
% IntensityThreshold - Intensity comparison threshold
% MaximumAngleThreshold - Maximum angle in degrees to be considered
% corner
% CornerLocationOutputPort - Enables output of the corner location
% MetricMatrixOutputPort - Enables output of the metric matrix
% MaximumCornerCount - Maximum number of corners to detect
% CornerThreshold - Minimum metric value that indicates a corner
% NeighborhoodSize - Size of suppressed region around detected
% corner
%
% This System object supports fixed-point operations. For more
% information, type vision.CornerDetector.helpFixedPoint.
%
% Example
% -------
% % Detect corners in an input image.
% I = im2single(imread('circuit.tif'));
% % select FAST algorithm by Rosten & Drummond
% cornerDetector = vision.CornerDetector( ...
% 'Method', 'Local intensity comparison (Rosten & Drummond)');
%
% pts = step(cornerDetector, I);
% % note that color data range must match the data range of image I
% color = [1 0 0]; % [red, green, blue]
% % insert color marker
% J = insertMarker(I, pts, 'Color', 'red');
% imshow(J); title ('Corners detected in a grayscale image');
%
% See also detectHarrisFeatures, detectMinEigenFeatures,
% detectBRISKFeatures, detectFASTFeatures.
end
function getNumOutputsImpl(in) %#ok<MANU>
end
function helpFixedPoint(in) %#ok<MANU>
%helpFixedPoint Display vision.CornerDetector System object fixed-point information
% vision.CornerDetector.helpFixedPoint displays information about
% fixed-point properties and operations of the vision.CornerDetector
% System object.
end
function isInactivePropertyImpl(in) %#ok<MANU>
end
function isInputComplexityLockedImpl(in) %#ok<MANU>
end
function isInputSizeLockedImpl(in) %#ok<MANU>
end
function isOutputComplexityLockedImpl(in) %#ok<MANU>
end
function loadObjectImpl(in) %#ok<MANU>
end
function processTunedPropertiesImpl(in) %#ok<MANU>
end
function resetImpl(in) %#ok<MANU>
end
function saveObjectImpl(in) %#ok<MANU>
end
function setupImpl(in) %#ok<MANU>
end
function stepImpl(in) %#ok<MANU>
end
function validateInputsImpl(in) %#ok<MANU>
end
function validatePropertiesImpl(in) %#ok<MANU>
% Check that at least one of the outputs is enabled
end
end
methods (Abstract)
end
properties
%AccumulatorDataType Accumulator word- and fraction-length designations
% Specify the accumulator fixed-point data type as one of ['Same as
% input' | {'Custom'}].
AccumulatorDataType;
%CoefficientsDataType Coefficients word- and fraction-length designations
% Specify the coefficients fixed-point data type as one of ['Same word
% length as input' | {'Custom'}]. This property is applicable when the
% Method property is not 'Local intensity comparison (Rosten &
% Drummond)'.
CoefficientsDataType;
%CornerLocationOutputPort Enables output of the corner location
% Set this property to true to output the corner location after corner
% detection. Both this property and MetricMatrixOutputPort property
% cannot be false at the same time. The default value for this property
% is true.
CornerLocationOutputPort;
%CornerThreshold Minimum metric value that indicates a corner
% Specify the minimum metric value that indicates a corner as a
% positive scalar number. The default value of this property is 0.0005.
% This property is applicable when the CornerLocationOutputPort
% property is true. This property is tunable.
CornerThreshold;
%CustomAccumulatorDataType Accumulator word and fraction lengths
% Specify the accumulator fixed-point type as an auto-signed, scaled
% numerictype object. This property is applicable when the
% AccumulatorDataType property is 'Custom'. The default value of this
% property is numerictype([],32,0).
%
% See also numerictype.
CustomAccumulatorDataType;
%CustomCoefficientsDataType Coefficients word and fraction lengths
% Specify the coefficients fixed-point type as an auto-signed
% numerictype object. This property is applicable when the Method
% property is not 'Local intensity comparison (Rosten & Drummond)' and
% the CoefficientsDataType property is 'Custom'. The default value of
% this property is numerictype([],16).
%
% See also numerictype.
CustomCoefficientsDataType;
%CustomMemoryDataType Memory word and fraction lengths
% Specify the memory fixed-point type as an auto-signed, scaled
% numerictype object. This property is applicable when the Method
% property is not 'Local intensity comparison (Rosten & Drummond)' and
% the MemoryDataType property is 'Custom'. The default value of this
% property is numerictype([],32,0).
%
% See also numerictype.
CustomMemoryDataType;
%CustomMetricOutputDataType Metric output word and fraction lengths
% Specify the metric output fixed-point type as an auto-signed, scaled
% numerictype object. This property is applicable when the
% MetricOutputDataType property is 'Custom'. The default value of this
% property is numerictype([],32,0).
%
% See also numerictype.
CustomMetricOutputDataType;
%CustomProductDataType Product word and fraction lengths
% Specify the product fixed-point type as an auto-signed, scaled
% numerictype object. This property is applicable when the Method
% property is not 'Local intensity comparison (Rosten & Drummond)' and
% the ProductDataType property is 'Custom'. The default value of this
% property is numerictype([],32,0).
%
% See also numerictype.
CustomProductDataType;
%IntensityThreshold Intensity comparison threshold
% Specify the intensity threshold value used to find valid bright or
% dark surrounding pixels, as a positive scalar. The default value of
% this property is 0.1. This property is applicable when the Method
% property is 'Local intensity comparison (Rosten & Drummond)'. This
% property is tunable.
IntensityThreshold;
%MaximumAngleThreshold Maximum angle in degrees to be considered corner
% Specify the maximum angle in degrees to indicate a corner as one of
% ['22.5' | '45.0' | '67.5' | '90.0' | '112.5' | '135.0' | {'157.5'}].
% This property is applicable when the Method property is 'Local
% intensity comparison (Rosten & Drummond)'.
MaximumAngleThreshold;
%MaximumCornerCount Maximum number of corners to detect
% Specify the maximum number of corners to detect as a positive scalar
% integer value. The default value of this property is 200. This
% property is applicable when the CornerLocationOutputPort property is
% true.
MaximumCornerCount;
%MemoryDataType Memory word- and fraction-length designations
% Specify the memory fixed-point data type as one of ['Same as input' |
% {'Custom'}]. This property is applicable when the Method property
% is not 'Local intensity comparison (Rosten & Drummond)'.
MemoryDataType;
%Method Method to find corner values
% Specify the method to find the corner values as one of [{'Harris
% corner detection (Harris & Stephens)'} | 'Minimum eigenvalue (Shi &
% Tomasi)' | 'Local intensity comparison (Rosten & Drummond)'].
Method;
%MetricMatrixOutputPort Enables output of the metric matrix
% Set this property to true to output the metric matrix after corner
% detection. Both this property and CornerLocationOutputPort property
% cannot be false at the same time. The default value for this property
% is false.
MetricMatrixOutputPort;
%MetricOutputDataType Metric output word- and fraction-length designations
% Specify the metric output fixed-point data type as one of [{'Same as
% accumulator'} | 'Same as input' | 'Custom'].
MetricOutputDataType;
%NeighborhoodSize Size of suppressed region around detected corner
% Specify the size of the neighborhood around the corner metric value
% over which the object zeros out the values, as a two element vector
% of positive odd integers, [r c]. Here, r is the number of rows in the
% neighborhood and c is the number of columns. The default value of
% this property is [11 11]. This property is applicable when the
% CornerLocationOutputPort property is true.
NeighborhoodSize;
%OverflowAction Overflow action for fixed-point operations
% Specify the overflow action as one of [{'Wrap'} | 'Saturate'].
OverflowAction;
%ProductDataType Product word- and fraction-length designations
% Specify the product fixed-point data type as one of ['Same as input'
% | {'Custom'}]. This property is applicable when the Method property
% is not 'Local intensity comparison (Rosten & Drummond)'.
ProductDataType;
%RoundingMethod Rounding method for fixed-point operations
% Specify the rounding method as one of ['Ceiling' | 'Convergent' |
% {'Floor'} | 'Nearest' | 'Round' | 'Simplest' | 'Zero'].
RoundingMethod;
%Sensitivity Sensitivity factor to detect sharp corners
% Specify the sensitivity factor, k, used in the Harris corner
% detection algorithm as a scalar numeric value, such that 0 < k < 0.25.
% The smaller the value of k, the more likely it is that the algorithm
% will detect sharp corners. The default value of this property is
% 0.04. This property is applicable when the Method property is 'Harris
% corner detection (Harris & Stephens)'. This property is tunable.
Sensitivity;
%SmoothingFilterCoefficients Coefficients of smoothing filter
% Specify the filter coefficients for the separable smoothing filter as
% a real-valued numeric vector. The vector must have an odd number of
% elements and a length of at least 3. The default value of this
% property is the output of fspecial('gaussian', [1 5], 1.5). For more
% information, type help fspecial. This property is applicable when the
% Method property is either 'Harris corner detection (Harris &
% Stephens)' or 'Minimum eigenvalue (Shi & Tomasi)'.
%
% See also help fspecial.
SmoothingFilterCoefficients;
end
end