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opencv-wasm

gapi_goodFeaturesToTrack

gapifunctionOpenCV 5.0.0
import { gapi_goodFeaturesToTrack } from '@banou/opencv-wasm'

Use after await initOpenCV(). See the initialization and named imports guide.

ARGUMENTSimage, maxCorners, qualityLevel, minDistance
FUNCTIONgapi_goodFeaturesToTrack
RETURN TYPEGArray_Point2f
Call structure. A void return can still write to destination arguments. The parameter descriptions define inputs, outputs and ownership.

Determines strong corners on an image.

The function finds the most prominent corners in the image or in the specified image region, as described in [Shi94]

  • Function calculates the corner quality measure at every source image pixel using the #cornerMinEigenVal or #cornerHarris .
  • Function performs a non-maximum suppression (the local maximums in 3 x 3 neighborhood are retained).
  • The corners with the minimal eigenvalue less than \texttt{qualityLevel} \cdot \max_{x,y} qualityMeasureMap(x,y) are rejected.
  • The remaining corners are sorted by the quality measure in the descending order.
  • Function throws away each corner for which there is a stronger corner at a distance less than maxDistance.

The function can be used to initialize a point-based tracker of an object.

Note: - If the function is called with different values A and B of the parameter qualityLevel , and A > B, the vector of returned corners with qualityLevel=A will be the prefix of the output vector with qualityLevel=B .

  • Function textual ID is "org.opencv.imgproc.feature.goodFeaturesToTrack"
gapi_goodFeaturesToTrack(image: GMat, maxCorners: number, qualityLevel: number, minDistance: number, mask: Mat, blockSize: number, useHarrisDetector: boolean, k: number): GArray_Point2f;
5 available overloads
gapi_goodFeaturesToTrack(image: GMat, maxCorners: number, qualityLevel: number, minDistance: number): GArray_Point2f;
gapi_goodFeaturesToTrack(image: GMat, maxCorners: number, qualityLevel: number, minDistance: number, mask: Mat): GArray_Point2f;
gapi_goodFeaturesToTrack(image: GMat, maxCorners: number, qualityLevel: number, minDistance: number, mask: Mat, blockSize: number): GArray_Point2f;
gapi_goodFeaturesToTrack(image: GMat, maxCorners: number, qualityLevel: number, minDistance: number, mask: Mat, blockSize: number, useHarrisDetector: boolean): GArray_Point2f;
gapi_goodFeaturesToTrack(image: GMat, maxCorners: number, qualityLevel: number, minDistance: number, mask: Mat, blockSize: number, useHarrisDetector: boolean, k: number): GArray_Point2f;
image

Input 8-bit or floating-point 32-bit, single-channel image.

maxCorners

Maximum number of corners to return. If there are more corners than are found, the strongest of them is returned. maxCorners <= 0 implies that no limit on the maximum is set and all detected corners are returned.

qualityLevel

Parameter characterizing the minimal accepted quality of image corners. The parameter value is multiplied by the best corner quality measure, which is the minimal eigenvalue (see #cornerMinEigenVal ) or the Harris function response (see #cornerHarris ). The corners with the quality measure less than the product are rejected. For example, if the best corner has the quality measure = 1500, and the qualityLevel=0.01 , then all the corners with the quality measure less than 15 are rejected.

minDistance

Minimum possible Euclidean distance between the returned corners.

mask

Optional region of interest. If the image is not empty (it needs to have the type CV_8UC1 and the same size as image ), it specifies the region in which the corners are detected.

blockSize

Size of an average block for computing a derivative covariation matrix over each pixel neighborhood. See cornerEigenValsAndVecs .

useHarrisDetector

Parameter indicating whether to use a Harris detector (see #cornerHarris) or #cornerMinEigenVal.

k

Free parameter of the Harris detector.

Returns

vector of detected corners. Release returned native handles with using or delete(), including handles nested in results.

Upstream declaration ↗

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.