{% extends "base.html" %} {% block title %} goodFeaturesToTrack {% endblock %} {% block description %}
Determines strong corners on an image.
{% endblock %} {% block signature %}cv2.goodFeaturesToTrack(image, maxCorners, qualityLevel, minDistance[, corners[, mask[, blockSize[, useHarrisDetector[, k]]]]]) → corners{% endblock %} {% block parameters %}
maxCorners=0
implies that no limit on the maximum is set and all detected corners are returned.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 qualityLevel=0.01
, then all the corners with the quality measure less than 15 are rejected.CV_8UC1
and the same size as image
), it specifies the region in which the corners are detected. Default is None.cornerEigenValsAndVecs
. Default is 3.cornerHarris
) or cornerMinEigenVal
. Default is False.k=0.04
.The function finds the most prominent corners in the image or in the specified image region, as described in [215].
cornerMinEigenVal
or cornerHarris
.maxDistance
.qualityLevel
and A > B, the vector of returned corners with qualityLevel=A
will be the prefix of the output vector with qualityLevel=B
.