master d0977d277664 cached
21 files
5.0 MB
1.3M tokens
1 requests
Download .txt
Showing preview only (5,275K chars total). Download the full file or copy to clipboard to get everything.
Repository: deepanshut041/feature-detection
Branch: master
Commit: d0977d277664
Files: 21
Total size: 5.0 MB

Directory structure:
gitextract_3u0q27xl/

├── .gitignore
├── README.md
├── brief/
│   ├── README.md
│   ├── brief.ipynb
│   └── brief.py
├── fast/
│   ├── README.md
│   ├── fast.ipynb
│   └── fast.py
├── harris/
│   ├── README.md
│   ├── harris.ipynb
│   └── harris.py
├── orb/
│   ├── README.md
│   ├── orb.ipynb
│   └── orb.py
├── requirements.txt
├── sift/
│   ├── README.md
│   ├── sift.ipynb
│   └── sift.py
└── surf/
    ├── README.md
    ├── surf.ipynb
    └── surf.py

================================================
FILE CONTENTS
================================================

================================================
FILE: .gitignore
================================================
*/.ipynb_checkpoints
.vscode

================================================
FILE: README.md
================================================

# Introduction To Feature Detection And Matching

Feature detection and matching is an important task in many computer vision applications, such as structure-from-motion, image retrieval, object detection, and more. In this series, we will be talking about local feature detection and matching.

<p align="center">   <img src="https://cdn-images-1.medium.com/max/2000/0*y8ZLm7kQiIIaUKpj.jpg" /> </p>


## Application Of Feature Detection And Matching

* Automate object tracking

* Point matching for computing disparity

* Stereo calibration(Estimation of the fundamental matrix)

* Motion-based segmentation

* Recognition

* 3D object reconstruction

* Robot navigation

* Image retrieval and indexing

## Feature

A feature is a piece of information which is relevant for solving the computational task related to a certain application. Features may be specific structures in the image such as points, edges or objects. Features may also be the result of a general neighborhood operation or feature detection applied to the image. The features can be classified into two main categories:

* The features that are in specific locations of the images, such as mountain peaks, building corners, doorways, or interestingly shaped patches of snow. These kinds of localized features are often called **keypoint features **(or even corners) and are often described by the appearance of patches of pixels surrounding the point location.

* The features that can be matched based on their orientation and local appearance (edge profiles) are called **edges** and they can also be good indicators of object boundaries and occlusion events in the image sequence.

## Main Component Of Feature Detection And Matching

* **Detection:** Identify the **Interest Point**

* **Description:** The local appearance around each feature point is described in some way that is (ideally) invariant under changes in illumination, translation, scale, and in-plane rotation. We typically end up with a descriptor vector for each feature point.

* **Matching:** Descriptors are compared across the images, to identify similar features. For two images we may get a set of pairs (***Xi, Yi***) ↔ (***Xi`, Yi`***), where (***Xi, Yi***) is a feature in one image and (***Xi`, Yi`***) its matching feature in the other image.

## Interest Point

Interest point or Feature Point is the point which is expressive in texture. Interest point is the point at which the direction of the boundary of the object changes abruptly or intersection point between two or more edge segments.

<p align="center">   <img src="https://cdn-images-1.medium.com/max/2040/0*Gw6TQyLYly_vEw94.jpg" /> </p>

### Properties Of Interest Point

* It has a well-defined *position* in image space or well localized.

* It is *stable* under local and global perturbations in the image domain as illumination/brightness variations, such that the interest points can be reliably computed with a high degree of *repeatability*.

* Should provide efficient detection.

### Possible Approaches

* Based on the brightness of an image(Usually by image derivative).

* Based on Boundary extraction(Usually by Edge detection and Curvature analysis).

### Algorithms for Identification

* Harris Corner

* SIFT(Scale Invariant Feature Transform)

* SURF(Speeded Up Robust Feature)

* FAST(Features from Accelerated Segment Test)

* ORB(Oriented FAST and Rotated BRIEF)

## Feature Descriptor

A feature descriptor is an algorithm which takes an image and outputs feature descriptors/feature vectors. Feature descriptors encode interesting information into a series of numbers and act as a sort of numerical “fingerprint” that can be used to differentiate one feature from another.

<p align="center">   <img src="https://cdn-images-1.medium.com/max/2000/1*UqpTAesCJHYJZJw9PpN2ZQ.jpeg" /> </p>

Ideally, this information would be invariant under image transformation, so we can find the feature again even if the image is transformed in some way. After detecting interest point we go on to compute a descriptor for every one of them. Descriptors can be categorized into two classes:

* **Local Descriptor:** It is a compact representation of a point’s local neighborhood. Local descriptors try to resemble shape and appearance only in a local neighborhood around a point and thus are very suitable for representing it in terms of matching.

* **Global Descriptor**: A global descriptor describes the whole image. They are generally not very robust as a change in part of the image may cause it to fail as it will affect the resulting descriptor.

### Algorithms

* SIFT(Scale Invariant Feature Transform)

* SURF(Speeded Up Robust Feature)

* BRISK (Binary Robust Invariant Scalable Keypoints)

* BRIEF (Binary Robust Independent Elementary Features)

* ORB(Oriented FAST and Rotated BRIEF)

## Features Matching

Features matching or generally image matching, a part of many computer vision applications such as image registration, camera calibration and object recognition, is the task of establishing correspondences between two images of the same scene/object. A common approach to image matching consists of detecting a set of interest points each associated with image descriptors from image data. Once the features and their descriptors have been extracted from two or more images, the next step is to establish some preliminary feature matches between these images.

<p align="center">   <img src="https://cdn-images-1.medium.com/max/2800/0*k--ZodnKi7ENH4MX.png" /> </p>

Generally, the performance of matching methods based on interest points depends on both the properties of the underlying interest points and the choice of associated image descriptors. Thus, detectors and descriptors appropriate for images contents shall be used in applications. For instance, if an image contains bacteria cells, the blob detector should be used rather than the corner detector. But, if the image is an aerial view of a city, the corner detector is suitable to find man-made structures. Furthermore, selecting a detector and a descriptor that addresses the image degradation is very important.

### Algorithms

* Brute-Force Matcher

* FLANN(Fast Library for Approximate Nearest Neighbors) Matcher

## Algorithm For Feature Detection And Matching

* Find a set of distinctive keypoints

* Define a region around each keypoint

* Extract and normalize the region content

* Compute a local descriptor from the normalized region

* Match local descriptors


## Thanks for reading! If you enjoyed it subscribe to updates on [my website](http://deepanshut041.github.io)! It would mean a lot to me and encourage me to write more stories like this.


================================================
FILE: brief/README.md
================================================
# Introduction to BRIEF(Binary Robust Independent Elementary Features)

Feature point descriptors are now at the core of many Computer Vision technologies, such as object recognition, 3D reconstruction, image retrieval, and camera localization. Since applications of these technologies have to handle ever more data or to run on mobile devices with limited computational resources, there is a growing need for local descriptors that are fast to compute, fast to match, and memory efficient.

<p align="center">
  <img src="https://cdn-images-1.medium.com/max/2000/0*iA-pC5LfbTcTgAcS" />
</p>

In this article, we use binary strings as an efficient feature point descriptor, which is called BRIEF. BRIEF is very fast both to build and to match.BRIEF easily outperforms other fast descriptors such as SURF and SIFT in terms of speed and terms of recognition rate in many cases.

## Background

After detecting keypoint we go on to compute a descriptor for every one of them. Feature descriptors encode interesting information into a series of numbers and act as a sort of numerical “fingerprint” that can be used to differentiate one feature from another. The defined neighborhood around pixel(keypoint) is known as a patch, which is a square of some pixel width and height.

<p align="center">
  <img src="https://cdn-images-1.medium.com/max/2976/1*lZ1sloEeHwZ3tXw4InCZJw.png" />
</p>

Image patches could be effectively classified on the basis of a relatively small number of pair-wise intensity comparisons. Brief convert image patches into a binary feature vector so that together they can represent an object. Binary features vector also know as binary feature descriptor is a feature vector that only contains 1 and 0. In brief  each keypoint is described by a feature vector which is 128–512 bits string.

<p align="center">
  <img src="https://cdn-images-1.medium.com/max/NaN/1*XWpgdt4Z4xeT-g8hn5JLsA.png" />
</p>

## **Smoothing Kernels**

Brief deals with the image at pixel level so it is very noise-sensitive. By pre-smoothing the patch, this sensitivity can be reduced, thus increasing the stability and repeatability of the descriptors. It is for the same reason that images need to be smoothed before they can be meaningfully differentiated when looking for edges.

<p align="center">
  <img src="https://cdn-images-1.medium.com/max/2000/0*dPQZlNjW3bcO0jES.jpg" />
</p>

Brief uses Gaussian kernel for smoothing image. In the figure below we comparison of Gaussian smoothing on the recognition rates for variances of Gaussian kernel ranging from 0 to 3. The more difficult the matching, the more important smoothing becomes to achieving good performance. The recognition rates remain relatively constant in the 1 to 3 range and, in practice, we use a value of 2.

<p align="center">
  <img src="https://cdn-images-1.medium.com/max/2000/1*hCHYVWW0CJHEP1ie9IwP0g.jpeg" />
</p>

## Smoothed Image to Binary Feature Vector

Now we have smoothed image patch, p. Now our target is to create a binary feature vector out of this patch. We simply create a binary feature vector of the binary test(τ) responses. A binary test τ is defined by:

<p align="center">
  <img src="https://cdn-images-1.medium.com/max/2292/1*4OnDKy41p6ycUmhIaE_xIQ.png" />
</p>

where p(x) is the intensity of p at a point x. Choosing a set of **n(**x,y**)**-location pairs uniquely defines a set of binary tests. Where **n** is the length of the binary feature vector and it could be 128, 256, and 512.

### How to select (x, y) pairs?

Generating a length **n** bit vector leaves many options for selecting the test locations((x, y) pair). The (x,y) pair is also called random pair which is located inside the patch. Total we have to select **n** test(random pair) for creating a binary feature vector and we have to choose this **n** test from one of five approaches(Sampling Geometries) given below.

<p align="center">
  <img src="https://cdn-images-1.medium.com/max/2000/0*bTfQfO4qOxk3qL78" />
</p>

Let consider the size of patch p is (S x S) and assuming keypoint is located in the center of the patch.

1. **Uniform(G I)**: Both x and y pixels in the random pair is drawn from a Unifrom distribution or spread of **S/2 around keypoint**. The pair(test) can lie close to the patch border.

1. **Gaussian(G II)**: Both x and y pixels in the random pair is drawn from a Gaussian distribution or spread of **0.04 * S² around keypoint**.

1. **Gaussian(G III)**: The first pixel(x) in the random pair is drawn from a Gaussian distribution centered around the **keypoint** with a stranded deviation or spread of **0.04 * S²**. The second pixel(y) in the random pair is drawn from a Gaussian distribution centered around the **first pixel(x) **with a standard deviation or spread of **0.01 * S²**. This forces the test(pair) to be more local. Test(pair) locations outside the patch are clamped to the edge of the patch.

1. **Coarse Polar Grid(G IV):** Both x and y pixels in the random pair is sampled from discrete locations of a coarse polar grid introducing a spatial quantization.

1. **Coarse Polar Grid(G V):** The first pixel(x) in random pair is at (0, 0) and the second pixel(y) in the random pair is drawn from discrete locations of a coarse polar grid.

<p align="center">
  <img src="https://cdn-images-1.medium.com/max/2000/0*k0oja80SnH9p8fqe.png" />
</p>

Finally, our BRIEF descriptor look like:

<p align="center">
  <img src="https://cdn-images-1.medium.com/max/2000/1*YIpY-B3oQCg6CQgpxpHipg.png" />
</p>

## Advantages of BRIEF

Brief relies on a relatively small number of intensity difference tests to represent an image patch as a binary string. Not only is construction and matching for this descriptor much faster than for other state-of-the-art ones, but it also tends to yield higher recognition rates, as long as invariance to large in-plane rotations is not a requirement.


## References

* [https://docs.opencv.org/3.1.0/dc/d7d/tutorial_py_brief.html](https://docs.opencv.org/3.1.0/dc/d7d/tutorial_py_brief.html)

* [https://in.udacity.com/course/computer-vision-nanodegree--nd891](https://in.udacity.com/course/computer-vision-nanodegree--nd891)

* [https://gilscvblog.com/2013/09/19/a-tutorial-on-binary-descriptors-part-2-the-brief-descriptor/](https://gilscvblog.com/2013/09/19/a-tutorial-on-binary-descriptors-part-2-the-brief-descriptor/)

* [https://www.researchgate.net/publication/221304115_BRIEF_Binary_Robust_Independent_Elementary_Features](https://www.researchgate.net/publication/221304115_BRIEF_Binary_Robust_Independent_Elementary_Features)

## Thanks for reading! If you enjoyed it, hit that clap button below and subscribe to updates on [my website](http://deepanshut041.github.io)! It would mean a lot to me and encourage me to write more stories like this.


================================================
FILE: brief/brief.ipynb
================================================
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# BRIEF(Binary Robust Independent Elementary Features)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import resources and display image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fbb10abd710>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
Download .txt
gitextract_3u0q27xl/

├── .gitignore
├── README.md
├── brief/
│   ├── README.md
│   ├── brief.ipynb
│   └── brief.py
├── fast/
│   ├── README.md
│   ├── fast.ipynb
│   └── fast.py
├── harris/
│   ├── README.md
│   ├── harris.ipynb
│   └── harris.py
├── orb/
│   ├── README.md
│   ├── orb.ipynb
│   └── orb.py
├── requirements.txt
├── sift/
│   ├── README.md
│   ├── sift.ipynb
│   └── sift.py
└── surf/
    ├── README.md
    ├── surf.ipynb
    └── surf.py
Condensed preview — 21 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (5,278K chars).
[
  {
    "path": ".gitignore",
    "chars": 28,
    "preview": "*/.ipynb_checkpoints\n.vscode"
  },
  {
    "path": "README.md",
    "chars": 6673,
    "preview": "\n# Introduction To Feature Detection And Matching\n\nFeature detection and matching is an important task in many computer "
  },
  {
    "path": "brief/README.md",
    "chars": 6777,
    "preview": "# Introduction to BRIEF(Binary Robust Independent Elementary Features)\n\nFeature point descriptors are now at the core of"
  },
  {
    "path": "brief/brief.ipynb",
    "chars": 1022196,
    "preview": "{\n \"cells\": [\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"# BRIEF(Binary Robust Independent E"
  },
  {
    "path": "brief/brief.py",
    "chars": 3189,
    "preview": "# # BRIEF(Binary Robust Independent Elementary Features)\n\n# ## Import resources and display image\n\nimport cv2\nimport mat"
  },
  {
    "path": "fast/README.md",
    "chars": 6712,
    "preview": "\n# Introduction to FAST (Features from Accelerated Segment Test)\n\nWe have several feature detectors and many of them are"
  },
  {
    "path": "fast/fast.ipynb",
    "chars": 726364,
    "preview": "{\n \"cells\": [\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"# Introduction to FAST (Features fr"
  },
  {
    "path": "fast/fast.py",
    "chars": 1852,
    "preview": "#  Introduction to FAST (Features from Accelerated Segment Test)\nimport cv2\nimport matplotlib.pyplot as plt\nimport numpy"
  },
  {
    "path": "harris/README.md",
    "chars": 5964,
    "preview": "\n# Introduction to Harris Corner Detector\n\nHarris Corner Detector is a corner detection operator that is commonly used i"
  },
  {
    "path": "harris/harris.ipynb",
    "chars": 301508,
    "preview": "{\n \"cells\": [\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"# Harris Corner Detection\"\n   ]\n  }"
  },
  {
    "path": "harris/harris.py",
    "chars": 1306,
    "preview": "# # Harris Corner Detection\n\n\n# ### Import resources and display image\n\nimport matplotlib.pyplot as plt\nimport numpy as "
  },
  {
    "path": "orb/README.md",
    "chars": 9120,
    "preview": "\n# Introduction to ORB (Oriented FAST and Rotated BRIEF)\n\nOriented FAST and Rotated BRIEF (ORB) was developed at OpenCV "
  },
  {
    "path": "orb/orb.ipynb",
    "chars": 1033380,
    "preview": "{\n \"cells\": [\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 1,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"data\":"
  },
  {
    "path": "orb/orb.py",
    "chars": 2837,
    "preview": "import cv2\nimport matplotlib.pyplot as plt\nimport numpy as np\n\n# Load the image\nimage1 = cv2.imread('./images/face1.jpeg"
  },
  {
    "path": "requirements.txt",
    "chars": 118,
    "preview": "jupyter==1.0.0\nmatplotlib==3.0.3\nnotebook==5.7.6\nnumpy==1.16.2\nopencv-contrib-python==3.4.2.16\nopencv-python==3.4.2.16"
  },
  {
    "path": "sift/README.md",
    "chars": 9239,
    "preview": "\n# Introduction to SIFT( Scale Invariant Feature Transform)\n\nSIFT stands for Scale-Invariant Feature Transform and was f"
  },
  {
    "path": "sift/sift.ipynb",
    "chars": 1051401,
    "preview": "{\n \"cells\": [\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"# SIFT (Scale-Invariant Feature Tra"
  },
  {
    "path": "sift/sift.py",
    "chars": 3008,
    "preview": "# # SIFT (Scale-Invariant Feature Transform)\n\n# ## Import resources and display image\n\nimport cv2\nimport matplotlib.pypl"
  },
  {
    "path": "surf/README.md",
    "chars": 8914,
    "preview": "# Introduction to SURF (Speeded-Up Robust Features)\n\nThe SURF method (Speeded Up Robust Features) is a fast and robust a"
  },
  {
    "path": "surf/surf.ipynb",
    "chars": 1067445,
    "preview": "{\n \"cells\": [\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"# SURF (Speeded-Up Robust Features)"
  },
  {
    "path": "surf/surf.py",
    "chars": 3004,
    "preview": "# # SURF (Speeded-Up Robust Features)\n\n\n# ## Import resources and display image\n\nimport cv2\nimport matplotlib.pyplot as "
  }
]

About this extraction

This page contains the full source code of the deepanshut041/feature-detection GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 21 files (5.0 MB), approximately 1.3M tokens. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.

Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.

Copied to clipboard!