Object Detection with Python using OpenCV: Introduction to computer vision
Object detection is a computer vision task that involves detecting and localizing objects within an image. This task is of great importance in many applications such as self-driving cars, surveillance systems, and object recognition. OpenCV is an open-source computer vision library that provides a variety of functions to perform object detection tasks.
OpenCV provides a variety of object detection algorithms that use different techniques such as feature-based, template matching, and deep learning-based approaches. Some of the popular object detection algorithms provided by OpenCV are:
- Cascade Classifier
- HOG (Histogram of Oriented Gradients) Detector
- DNN (Deep Neural Network) based Detector
Cascade Classifier: Cascade classifier is a traditional computer vision-based algorithm for object detection. It uses a Haar-like feature-based approach to detect objects. The algorithm involves training a classifier on positive and negative samples of the object to be detected. The trained classifier is then used to scan the input image and detect the object by matching the Haar-like features.
HOG Detector: HOG detector is a feature-based algorithm that uses the Histogram of Oriented Gradients (HOG)…