OpenCV  3.3.1-dev
Open Source Computer Vision
Classes | Functions
Feature Detection and Description

Classes

class  cv::AgastFeatureDetector
 Wrapping class for feature detection using the AGAST method. : More...
 
class  cv::AKAZE
 Class implementing the AKAZE keypoint detector and descriptor extractor, described in [5]. More...
 
class  cv::BRISK
 Class implementing the BRISK keypoint detector and descriptor extractor, described in [102] . More...
 
class  cv::FastFeatureDetector
 Wrapping class for feature detection using the FAST method. : More...
 
class  cv::GFTTDetector
 Wrapping class for feature detection using the goodFeaturesToTrack function. : More...
 
class  cv::KAZE
 Class implementing the KAZE keypoint detector and descriptor extractor, described in [6] . More...
 
class  cv::MSER
 Maximally stable extremal region extractor. More...
 
class  cv::ORB
 Class implementing the ORB (oriented BRIEF) keypoint detector and descriptor extractor. More...
 
class  cv::SimpleBlobDetector
 Class for extracting blobs from an image. : More...
 

Functions

void cv::AGAST (InputArray image, std::vector< KeyPoint > &keypoints, int threshold, bool nonmaxSuppression=true)
 
void cv::AGAST (InputArray image, std::vector< KeyPoint > &keypoints, int threshold, bool nonmaxSuppression, int type)
 Detects corners using the AGAST algorithm. More...
 
void cv::FAST (InputArray image, std::vector< KeyPoint > &keypoints, int threshold, bool nonmaxSuppression=true)
 
void cv::FAST (InputArray image, std::vector< KeyPoint > &keypoints, int threshold, bool nonmaxSuppression, int type)
 Detects corners using the FAST algorithm. More...
 

Detailed Description

Function Documentation

§ AGAST() [1/2]

void cv::AGAST ( InputArray  image,
std::vector< KeyPoint > &  keypoints,
int  threshold,
bool  nonmaxSuppression = true 
)

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

§ AGAST() [2/2]

void cv::AGAST ( InputArray  image,
std::vector< KeyPoint > &  keypoints,
int  threshold,
bool  nonmaxSuppression,
int  type 
)

Detects corners using the AGAST algorithm.

Parameters
imagegrayscale image where keypoints (corners) are detected.
keypointskeypoints detected on the image.
thresholdthreshold on difference between intensity of the central pixel and pixels of a circle around this pixel.
nonmaxSuppressionif true, non-maximum suppression is applied to detected corners (keypoints).
typeone of the four neighborhoods as defined in the paper: AgastFeatureDetector::AGAST_5_8, AgastFeatureDetector::AGAST_7_12d, AgastFeatureDetector::AGAST_7_12s, AgastFeatureDetector::OAST_9_16

For non-Intel platforms, there is a tree optimised variant of AGAST with same numerical results. The 32-bit binary tree tables were generated automatically from original code using perl script. The perl script and examples of tree generation are placed in features2d/doc folder. Detects corners using the AGAST algorithm by [115] .

§ FAST() [1/2]

void cv::FAST ( InputArray  image,
std::vector< KeyPoint > &  keypoints,
int  threshold,
bool  nonmaxSuppression = true 
)

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

§ FAST() [2/2]

void cv::FAST ( InputArray  image,
std::vector< KeyPoint > &  keypoints,
int  threshold,
bool  nonmaxSuppression,
int  type 
)

Detects corners using the FAST algorithm.

Parameters
imagegrayscale image where keypoints (corners) are detected.
keypointskeypoints detected on the image.
thresholdthreshold on difference between intensity of the central pixel and pixels of a circle around this pixel.
nonmaxSuppressionif true, non-maximum suppression is applied to detected corners (keypoints).
typeone of the three neighborhoods as defined in the paper: FastFeatureDetector::TYPE_9_16, FastFeatureDetector::TYPE_7_12, FastFeatureDetector::TYPE_5_8

Detects corners using the FAST algorithm by [152] .

Note
In Python API, types are given as cv2.FAST_FEATURE_DETECTOR_TYPE_5_8, cv2.FAST_FEATURE_DETECTOR_TYPE_7_12 and cv2.FAST_FEATURE_DETECTOR_TYPE_9_16. For corner detection, use cv2.FAST.detect() method.