Module opencv::features2d
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2D Features Framework
Feature Detection and Description
Descriptor Matchers
Matchers of keypoint descriptors in OpenCV have wrappers with a common interface that enables you to easily switch between different algorithms solving the same problem. This section is devoted to matching descriptors that are represented as vectors in a multidimensional space. All objects that implement vector descriptor matchers inherit the DescriptorMatcher interface.
Drawing Function of Keypoints and Matches
Object Categorization
This section describes approaches based on local 2D features and used to categorize objects.
Hardware Acceleration Layer
Modules
Structs
Brute-force descriptor matcher.
Class to compute an image descriptor using the bag of visual words.
kmeans -based class to train visual vocabulary using the bag of visual words approach. :
Flann-based descriptor matcher.
A class filters a vector of keypoints.
Enums
Constants
Output image matrix will be created (Mat::create),
i.e. existing memory of output image may be reused.
Two source image, matches and single keypoints will be drawn.
For each keypoint only the center point will be drawn (without
the circle around keypoint with keypoint size and orientation).
Output image matrix will not be created (Mat::create).
Matches will be drawn on existing content of output image.
For each keypoint the circle around keypoint with keypoint size and
orientation will be drawn.
Single keypoints will not be drawn.
Traits
Constant methods for crate::features2d::AKAZE
Class for implementing the wrapper which makes detectors and extractors to be affine invariant,
described as ASIFT in YM11 .
Constant methods for crate::features2d::AffineFeature
Wrapping class for feature detection using the AGAST method. :
Constant methods for crate::features2d::AgastFeatureDetector
Mutable methods for crate::features2d::BFMatcher
Constant methods for crate::features2d::BFMatcher
Mutable methods for crate::features2d::BOWImgDescriptorExtractor
Constant methods for crate::features2d::BOWImgDescriptorExtractor
Mutable methods for crate::features2d::BOWKMeansTrainer
Constant methods for crate::features2d::BOWKMeansTrainer
Abstract base class for training the bag of visual words vocabulary from a set of descriptors.
Constant methods for crate::features2d::BOWTrainer
Constant methods for crate::features2d::BRISK
Abstract base class for matching keypoint descriptors.
Constant methods for crate::features2d::DescriptorMatcher
Wrapping class for feature detection using the FAST method. :
Constant methods for crate::features2d::FastFeatureDetector
Mutable methods for crate::features2d::Feature2D
Constant methods for crate::features2d::Feature2D
Mutable methods for crate::features2d::FlannBasedMatcher
Constant methods for crate::features2d::FlannBasedMatcher
Wrapping class for feature detection using the goodFeaturesToTrack function. :
Constant methods for crate::features2d::GFTTDetector
Constant methods for crate::features2d::KAZE
Mutable methods for crate::features2d::KeyPointsFilter
Constant methods for crate::features2d::KeyPointsFilter
Maximally stable extremal region extractor
Constant methods for crate::features2d::MSER
Class implementing the ORB (oriented BRIEF) keypoint detector and descriptor extractor
Constant methods for crate::features2d::ORB
Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform
(SIFT) algorithm by D. Lowe Lowe04 .
Constant methods for crate::features2d::SIFT
Class for extracting blobs from an image. :
Constant methods for crate::features2d::SimpleBlobDetector
Functions
Detects corners using the AGAST algorithm
Detects corners using the AGAST algorithm
Draws keypoints.
Draws the found matches of keypoints from two images.
Draws the found matches of keypoints from two images.
C++ default parameters
Functions to evaluate the feature detectors and [generic] descriptor extractors * **
Detects corners using the FAST algorithm
Detects corners using the FAST algorithm
Type Definitions
Extractors of keypoint descriptors in OpenCV have wrappers with a common interface that enables you
to easily switch between different algorithms solving the same problem. This section is devoted to
computing descriptors represented as vectors in a multidimensional space. All objects that implement
the vector descriptor extractors inherit the DescriptorExtractor interface.
Feature detectors in OpenCV have wrappers with a common interface that enables you to easily switch
between different algorithms solving the same problem. All objects that implement keypoint detectors
inherit the FeatureDetector interface.