Categories: AI/ML Research

Image Feature Extraction in OpenCV: Edges and Corners

In the world of computer vision and image processing, the ability to extract meaningful features from images is important. These features serve as vital inputs for various downstream tasks, such as object detection and classification. There are multiple ways to find these features. The naive way is to count the pixels. But in OpenCV, there […]

The post Image Feature Extraction in OpenCV: Edges and Corners appeared first on MachineLearningMastery.com.

Image Feature Extraction in OpenCV: Keypoints and Description Vectors

In the previous post, you learned some basic feature extraction algorithms in OpenCV. The features are extracted in the form of classifying pixels. These indeed abstract the features from images because you do not need to consider the different color channels of each pixel, but to consider a single value.…

November 13, 2023

In "AI/ML Research"

Image Vector Representation for Machine Learning Using OpenCV

One of the pre-processing steps that are often carried out on images before feeding them into a machine learning algorithm is to convert them into a feature vector. As we will see in this tutorial, there are several advantages to converting an image into a feature vector that makes the…

November 24, 2023

In "AI/ML Research"

Extracting Histogram of Gradients with OpenCV

Besides the feature descriptor generated by SIFT, SURF, and ORB, as in the previous post, the Histogram of Oriented Gradients (HOG) is another feature descriptor you can obtain using OpenCV. HOG is a robust feature descriptor widely used in computer vision and image processing for object detection and recognition tasks.…

November 13, 2023

In "AI/ML Research"

AI Generated Robotic Content