1. SIFT Harris and Shi-Tomasi corner detection algorithms. These two algorithmshave rotation invariance but not scale invariance. Take the following figure as an example. Corners can be detected in the small image on the left. But after the image is enlarged and the same window is used, the corner points cannot be detected. Scale-invariant feature […]
Tag: sift
1 Comparison and implementation of matching methods based on SIFT image feature recognition
Comparison and implementation of matching methods based on SIFT image feature recognition 1 Matcher Selection Currently commonly used matchers include BFMatcher and FlannBasedMatcher 1.1 BFMatcher The full name of BFMatcher is Brute-Force Matcher (literally translated as violent matcher) General principle: For each descriptor in img1, BFMatcher compares it to all descriptors in img2; it calculates […]
SIFT (Scale-Invariant Feature Transform) in computer vision algorithms
Introduction Computer vision is one of the fields that has developed rapidly in recent years. It involves the understanding and analysis of images and videos. Image feature extraction is one of the important tasks in computer vision. SIFT (Scale-Invariant Feature Transform) is a commonly used image feature extraction algorithm. It has the characteristics of scale […]
Python Remote Sensing Image Processing Application Chapter 039 GDAL Remote Sensing Image Corner Detection (Harris, Shi-Tomasi, FAST, SIFT, SURF, ORB, MinEngen, Brisk) is being updated…
1. Corner detection method Remote sensing image corner detection is a method used to identify corner points (also called interest points) in images. Corner points usually represent significant feature points in the image. The following are some commonly used remote sensing image corner detection methods: Harris corner detection algorithm: The Harris algorithm determines whether the […]
Sift: small root heap (minpq.c)
SIFT code for Lowe,D Given the index of a node, find the corresponding indexes of its root and left and right children /* returns the array index of element i’s parent */ static inline int parent(int i) { return (i – 1) / 2;//Return the serial number of the parent node } /* returns the […]
96.sift feature point detection
Directory 1 What is SIFT 2 sift feature point detection principle 2.1 Principle explanation 2.2 Summary of SIFT detection process 3 Detailed explanation of API functions 3.1 SIFT::create() function 3.2 detectAndCompute() function 3.3 drawKeypoints() function 4 Implementation by writing code in C++ 1 What is SIFT SIFT is the scale-invariant feature transformation, which is used […]
Sift: (Step 4) Construct descriptors for keypoints
Previous step: sift: (third step) give direction to key points_zzz_zzzz_’s Blog-CSDN Blog I think the hardest thing to understand is this fourth step. It seems simple, but if you look into it carefully, you still need to think about it carefully. Let me talk about Purpose first: through the previous three steps, we have found […]
sift: (third step) assigning directions to key points
Previous step: Sift: (second step) determination of the key point position_zzz_zzzz_’s Blog-CSDN Blog Purpose: In order to make the keypoint descriptor invariant to rotation, it is necessary to use the local features of the image to assign a reference direction to each keypoint. In the second step, the key points have been found, and the […]
Sift: (Step 2) Determination of key point positions
Previous step: Sift: (the first step) to establish a Gaussian difference pyramid_zzz_zzzz_’s blog-CSDN blog The key points of the picture are often the points with stable properties, and the points containing more information are often in the position of extreme value First, thresholding The value of the current detection point should satisfy
Image feature matching – SIFT function application [opencv]
Table of Contents related functions sift. detectAndCompute cv.drawKeypoints cv.KeyPoint cv2.BFMatcher Related functions An important function of the SIFT (Scale-Invariant Feature Transform) algorithm in OpenCV. The SIFT algorithm is a classic method for image feature extraction and matching, which can extract feature points in an image with scale invariance, rotation invariance and partial view invariance strong> […]