ORB
import { ORB } from '@banou/opencv-wasm'Use after await initOpenCV(). See the initialization and named imports guide.
Native object: release it with using or delete(). Factories can return null; check before calling methods. Inherits Feature2D.
Class implementing the ORB (oriented BRIEF) keypoint detector and descriptor extractor
described in [RRKB11] . The algorithm uses FAST in pyramids to detect stable keypoints, selects the strongest features using FAST or Harris response, finds their orientation using first-order moments and computes the descriptors using BRIEF (where the coordinates of random point pairs (or k-tuples) are rotated according to the measured orientation).
Constructors and members
static create
The ORB constructor
create(nfeatures: number, scaleFactor: number, nlevels: number, edgeThreshold: number, firstLevel: number, WTA_K: number, scoreType: number, patchSize: number, fastThreshold: number): ORB | null;10 available overloads
create(): ORB | null;create(nfeatures: number): ORB | null;create(nfeatures: number, scaleFactor: number): ORB | null;create(nfeatures: number, scaleFactor: number, nlevels: number): ORB | null;create(nfeatures: number, scaleFactor: number, nlevels: number, edgeThreshold: number): ORB | null;create(nfeatures: number, scaleFactor: number, nlevels: number, edgeThreshold: number, firstLevel: number): ORB | null;create(nfeatures: number, scaleFactor: number, nlevels: number, edgeThreshold: number, firstLevel: number, WTA_K: number): ORB | null;create(nfeatures: number, scaleFactor: number, nlevels: number, edgeThreshold: number, firstLevel: number, WTA_K: number, scoreType: number): ORB | null;create(nfeatures: number, scaleFactor: number, nlevels: number, edgeThreshold: number, firstLevel: number, WTA_K: number, scoreType: number, patchSize: number): ORB | null;create(nfeatures: number, scaleFactor: number, nlevels: number, edgeThreshold: number, firstLevel: number, WTA_K: number, scoreType: number, patchSize: number, fastThreshold: number): ORB | null;nfeaturesThe maximum number of features to retain.
scaleFactorPyramid decimation ratio, greater than 1. scaleFactor==2 means the classical pyramid, where each next level has 4x less pixels than the previous, but such a big scale factor will degrade feature matching scores dramatically. On the other hand, too close to 1 scale factor will mean that to cover certain scale range you will need more pyramid levels and so the speed will suffer.
nlevelsThe number of pyramid levels. The smallest level will have linear size equal to input_image_linear_size/pow(scaleFactor, nlevels - firstLevel).
edgeThresholdThis is size of the border where the features are not detected. It should roughly match the patchSize parameter.
firstLevelThe level of pyramid to put source image to. Previous layers are filled with upscaled source image.
WTA_KThe number of points that produce each element of the oriented BRIEF descriptor. The default value 2 means the BRIEF where we take a random point pair and compare their brightnesses, so we get 0/1 response. Other possible values are 3 and 4. For example, 3 means that we take 3 random points (of course, those point coordinates are random, but they are generated from the pre-defined seed, so each element of BRIEF descriptor is computed deterministically from the pixel rectangle), find point of maximum brightness and output index of the winner (0, 1 or 2). Such output will occupy 2 bits, and therefore it will need a special variant of Hamming distance, denoted as NORM_HAMMING2 (2 bits per bin). When WTA_K=4, we take 4 random points to compute each bin (that will also occupy 2 bits with possible values 0, 1, 2 or 3).
scoreTypeThe default HARRIS_SCORE means that Harris algorithm is used to rank features (the score is written to KeyPoint::score and is used to retain best nfeatures features); FAST_SCORE is alternative value of the parameter that produces slightly less stable keypoints, but it is a little faster to compute.
patchSizesize of the patch used by the oriented BRIEF descriptor. Of course, on smaller pyramid layers the perceived image area covered by a feature will be larger.
fastThresholdthe fast threshold
The ORB | null result.
clone
Create another handle to the same native object. This retains the object without copying its pixels or algorithm state; dispose both handles separately.
clone(): this;The this result.
setMaxFeatures
Set the max features used by this ORB object.
setMaxFeatures(maxFeatures: number): void;maxFeaturesmax features argument (number).
getMaxFeatures
Return the max features configured on this ORB object.
getMaxFeatures(): number;The number result.
setScaleFactor
Set the scale factor used by this ORB object.
setScaleFactor(scaleFactor: number): void;scaleFactorscale factor argument (number).
getScaleFactor
Return the scale factor configured on this ORB object.
getScaleFactor(): number;The number result.
setNLevels
Set the nlevels used by this ORB object.
setNLevels(nlevels: number): void;nlevelsnlevels argument (number).
getNLevels
Return the nlevels configured on this ORB object.
getNLevels(): number;The number result.
setEdgeThreshold
Set the edge threshold used by this ORB object.
setEdgeThreshold(edgeThreshold: number): void;edgeThresholdedge threshold argument (number).
getEdgeThreshold
Return the edge threshold configured on this ORB object.
getEdgeThreshold(): number;The number result.
setFirstLevel
Set the first level used by this ORB object.
setFirstLevel(firstLevel: number): void;firstLevelfirst level argument (number).
getFirstLevel
Return the first level configured on this ORB object.
getFirstLevel(): number;The number result.
setWTA_K
Set the wta k used by this ORB object.
setWTA_K(wta_k: number): void;wta_kwta k argument (number).
getWTA_K
Return the wta k configured on this ORB object.
getWTA_K(): number;The number result.
setScoreType
Set the score type used by this ORB object.
setScoreType(scoreType: number): void;scoreTypescore type argument (number).
getScoreType
Return the score type configured on this ORB object.
getScoreType(): number;The number result.
setPatchSize
Set the patch size used by this ORB object.
setPatchSize(patchSize: number): void;patchSizepatch size argument (number).
getPatchSize
Return the patch size configured on this ORB object.
getPatchSize(): number;The number result.
setFastThreshold
Set the fast threshold used by this ORB object.
setFastThreshold(fastThreshold: number): void;fastThresholdfast threshold argument (number).
getFastThreshold
Return the fast threshold configured on this ORB object.
getFastThreshold(): number;The number result.
getDefaultName
Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.
getDefaultName(): string;The string result.
These signatures describe this package. Upstream documentation can mention optional backends that are absent from this build. Check runtime compatibility before choosing a backend or file format.