Introduction to OpenC

OpenCV is the most popular library for computer vision and image processing. ROS is an open-source, meta-operating system for your robot. It provides the services you would expect from an operating system, including hardware abstraction, low-level device control, implementation of commonly-used functionality, message-passing between processes, and package management. When we are developing a robot it is mandatory to be aware of the surrounding objects and what is happening in the environment. This is called ROBOT PERCEPTION. According to the robot perception the robot itself will plan the motion. Robot perception origin for computer vision. Computer vision includes methods for acquiring, processing, analyzing and understanding digital images. Typically robots use a camera to see the world around them. the camera provides the images which need to be processed so that it can extract useful information. Image processing is a very complex challenging task. Fortunately, in the last previous years a lot of research has been done and significant advances took place. It is now possible to accurately analyze the content of an image and extract useful information out of it. It provides a comprehensive set of tools and when it comes to perform complex operation of image processing. This article will help you to give and idea and overview about the openCV.

OpenCV

• Open source Computer vision library
• BSD license
• Free for both academic and commercial use
• It supports multiple programming languages namely C++ wife and Java and works under different operating
• systems including Windows Mac OS Linux iOS and Android.
• It has a strong focus on real time since it was written C++ and has been optimized open. Sivy can perform a lot of operations related to computer vision.
• 2d image processing
• GPU-Accelerated Computer Vision
• and much more

It can also form image input and output and video input output. It can read images from files it can read video streams coming from us be cameras from video files it can perform camera calibration video analysis like motional extract and feature tracking foreground extraction and nowadays with the advances of much learning and deep learning technology it is possible to accurately perform object detection and also recognition. OPEC also supports accelerated computer vision and it has much much more functionalities so let's see.

Image Segmentation

One of the basic functions of a PC is to do image segmentation. So image segmentation is the process of partitioning a digital image into multiple segments and it is used to locate objects and boundaries in images.

Image Threshold

It allows to transform a gray scale image to a binary image. So the idea here is to take a color as a shot and any color above the threshold will be considered as white and any color below the threshold will be considered as black. So the resulting image will be binary either black or white.

Object Detection and Recognition

With the advances of machine learning and deep neural networks it is not possible to detect and they recognize objects inside an image. And this technology has promoted a lot of applications like for example autonomous vehicles which rely on computer vision techniques to observe the world around them.

Drawing

It is also possible to do nice drawing with openCV. For example it's possible to draw circles lines polygon text and make different shapes.

Edge Detection

It consists in finding the boundaries of objects within the image and works by detecting discontinuities in brightness. Edge detection is used for image segmentation and data structure.

Video/Image Input and output

One of the very useful functionalities in AAPC is that to read and write images and videos trips up and TV it becomes very simple to read an image and load it into a data structure for further processing. This was a brief background.