In image processing, keypoints are points in an image that have strong local contrast or edges.
Keypoint-based methods are used to detect and describe objects in images. They are also used for object recognition tasks, such as finding a specific person in a crowd of people.
Now that we understand a little more about what keypoints are, let’s take a look at some of the most common varieties:
Scale Invariant Feature Transform (SIFT)
This detects scale-invariant features including corners, blobs, ridges, bends, and circles. It can be applied to any type of input image.
Its method of operation has been extensively researched and optimized. SIFT was first introduced by David Lowe in his 2004 paper “A Local Detector of Image Features” at the ICCV conference.
The method is based on a combination of gradient information and Hessian matrix calculation. This algorithm works well on natural images, but does not work well on artificial images.
Speeded Up Robust Features (SURF)
SURF is one of the most popular algorithms for feature detection. It was originally developed by Paul Viola and Michael Jones at the University of Toronto.
Their implementation of SURF is known as ORB. SURF uses integral image techniques to compute fast edge responses.
FAST is another popular algorithm. It was created by James Baker with Robert Harris and published in their 2000 paper. FAST is very similar to SURF.
Speeded up robust features (SURF) combines both SURF and FAST features. It was created by Jitendra Malik and Peter Robinson at Cambridge University.
Scale-Invariant Feature Transform (SIAT)
SIAT is essentially a variant of SIFT which attempts to address some limitations of SIFT.
It was created by John Canny et al. at Carnegie Mellon University. SIAT is designed to make it more effective at detecting small features compared to SIFT.
Harris Corner Detection
The next keypoint we’re looking at is a corner detector that calculates interest points using a Laplacian operator.
It was proposed by Stephen M. Davies at Queen Mary College, London. This technique is widely used because it is simple and effective.
Similar to the previous keypoint, edge histograms are a set of measurements taken along the boundary of an image.
They were invented by Yann LeCun and Yoshua Bengio at New York University. These features are useful when there are few distinct boundaries in an image.
Histogram Of Oriented Gradients (HOG)
HOG is another histogram, though this is one of the gradient orientations of the image.
HOG was patented by Ruslan Salakhutdinov at the Georgia Institute of Technology. HOG makes use of the fact that edges often appear as regions of large gradient changes.
Local Binary Patterns (LBP)
These are a class of texture descriptors. LBP was invented by Adela Pantic at IBM Zurich Research Laboratory.
Local Phase Quantization (LPQ)
This keypoint is a form of pattern matching that involves comparing the phases of two pixels. LPQ was invented by Marc Levoy at Stanford University.
Optical flow (OF)
This is a vector field that represents the apparent motion of objects between frames of video. OF was invented by Andrew Zisserman at Oxford University.
Region Proposal Network (RPN)
RPN is a convolutional neural network architecture for object proposal generation. RPN was invented by Jian Sun at Microsoft Research.
A saliency map is a visual attention mechanism where the region of an image that draws people’s attention is highlighted.
It was discovered by Christoph Koch at Max Planck Institute for Biological Cybernetics.
Structure From Motion (SFM)
SFM is a method for estimating 3D models of scenes from multiple images.
The first successful implementations were based on keypoint detectors, such as SURF and SIFT. Recent developments have focused on learning-based approaches.
Supervised Descent Method (SDM)
Not to be confused with SFM, SDM is a method for finding local minima of nonlinear functions. SDM was invented by David Mumford at MIT.
Surface Normal Map (SnMap)
Surface normal maps are a type of normal mapping that use surface normals instead of per vertex normals. SnMap was developed by Anton van den Brink at the Technical University of Delft.
Topological Structure Analysis (TSA)
Quite simply, topological structure analysis is another way of identifying different shapes within an image. TSA was invented by Martin Abadi at Imperial College, London.
Visual Odometry (VO)
VO is a set of algorithms for computing the pose (position and rotation) of a camera relative to other cameras or inertial sensors. VO was invented by Thore Graepel at ETH Zurich.
We can see that these methods vary greatly in terms of their complexity, accuracy, speed, and robustness. Some are very fast but not accurate enough, while others are slow and inaccurate.
Best Image Processing Software
Image processing is important for anyone involved in graphic design. These are some of the most popular and professional software used all over the world.
Adobe Photoshop has been around since 1987, and it is still going strong today. This program allows you to create amazing photos and graphics.
It also comes with many tools like filters, layers, actions, etc.
Illustrator is Adobe’s vector drawing tool. It is similar to CorelDraw and InDesign. You can easily edit text, draw paths, and make complex illustrations.
InDesign is Apple’s version of Illustrator. Like its rival, this program lets you create great-looking documents. It’s perfect if you need to create magazines, brochures, flyers, posters, books, and more.
Corel Draw is one of the best free photo editing programs out there. It offers an extensive library of brushes, textures, effects, and much more.
SketchBook is a powerful illustration app that allows you to create designs quickly. You can import your own photographs, sketch directly into the timeline, or even add video and audio clips.
Paint Tool SAI
PaintTool Sai is a simple yet powerful painting application. You can adjust colors, brush size, opacity, and much more. You can also save your work and share it online.
Gimp is a free, open-source alternative to Photoshop. It supports layers, color management, and almost anything you could want to do with a digital photo editor.
There are so many types of image editors available out there. Each one of them has its pros and cons. But overall, we think these are all pretty good.
As long as you know what you are doing, you will be able to achieve great results.
If you enjoyed this article, you might enjoy our post on ‘Is Inkscape Safe?‘.