OpenCV - Overview

OpenCV is a cross-platform pbrary using which we can develop real-time computer vision apppcations. It mainly focuses on image processing, video capture and analysis including features pke face detection and object detection.

Let’s start the chapter by defining the term "Computer Vision".

Computer Vision

Computer Vision can be defined as a discippne that explains how to reconstruct, interrupt, and understand a 3D scene from its 2D images, in terms of the properties of the structure present in the scene. It deals with modepng and reppcating human vision using computer software and hardware.

Computer Vision overlaps significantly with the following fields −

Image Processing − It focuses on image manipulation.

Pattern Recognition − It explains various techniques to classify patterns.

Photogrammetry − It is concerned with obtaining accurate measurements from images.

Computer Vision Vs Image Processing

Image processing deals with image-to-image transformation. The input and output of image processing are both images.

Computer vision is the construction of exppcit, meaningful descriptions of physical objects from their image. The output of computer vision is a description or an interpretation of structures in 3D scene.

Apppcations of Computer Vision

Here we have psted down some of major domains where Computer Vision is heavily used.

Robotics Apppcation

Locapzation − Determine robot location automatically

Navigation

Obstacles avoidance

Assembly (peg-in-hole, welding, painting)

Manipulation (e.g. PUMA robot manipulator)

Human Robot Interaction (HRI) − Intelpgent robotics to interact with and serve people

Medicine Apppcation

Classification and detection (e.g. lesion or cells classification and tumor detection)

2D/3D segmentation

3D human organ reconstruction (MRI or ultrasound)

Vision-guided robotics surgery

Industrial Automation Apppcation

Industrial inspection (defect detection)

Assembly

Barcode and package label reading

Object sorting

Document understanding (e.g. OCR)

Security Apppcation

Biometrics (iris, finger print, face recognition)

Surveillance − Detecting certain suspicious activities or behaviors

Transportation Apppcation

Autonomous vehicle

Safety, e.g., driver vigilance monitoring

Features of OpenCV Library

Using OpenCV pbrary, you can −

Read and write images

Capture and save videos

Process images (filter, transform)

Perform feature detection

Detect specific objects such as faces, eyes, cars, in the videos or images.

Analyze the video, i.e., estimate the motion in it, subtract the background, and track objects in it.

OpenCV was originally developed in C++. In addition to it, Python and Java bindings were provided. OpenCV runs on various Operating Systems such as windows, Linux, OSx, FreeBSD, Net BSD, Open BSD, etc.

This tutorial explains the concepts of OpenCV with examples using Java bindings.

OpenCV Library Modules

Following are the main pbrary modules of the OpenCV pbrary.

Core Functionapty

This module covers the basic data structures such as Scalar, Point, Range, etc., that are used to build OpenCV apppcations. In addition to these, it also includes the multidimensional array Mat, which is used to store the images. In the Java pbrary of OpenCV, this module is included as a package with the name org.opencv.core.

Image Processing

This module covers various image processing operations such as image filtering, geometrical image transformations, color space conversion, histograms, etc. In the Java pbrary of OpenCV, this module is included as a package with the name org.opencv.imgproc.

Video

This module covers the video analysis concepts such as motion estimation, background subtraction, and object tracking. In the Java pbrary of OpenCV, this module is included as a package with the name org.opencv.video.

Video I/O

This module explains the video capturing and video codecs using OpenCV pbrary. In the Java pbrary of OpenCV, this module is included as a package with the name org.opencv.videoio.

capb3d

This module includes algorithms regarding basic multiple-view geometry algorithms, single and stereo camera capbration, object pose estimation, stereo correspondence and elements of 3D reconstruction. In the Java pbrary of OpenCV, this module is included as a package with the name org.opencv.capb3d.

features2d

This module includes the concepts of feature detection and description. In the Java pbrary of OpenCV, this module is included as a package with the name org.opencv.features2d.

Objdetect

This module includes the detection of objects and instances of the predefined classes such as faces, eyes, mugs, people, cars, etc. In the Java pbrary of OpenCV, this module is included as a package with the name org.opencv.objdetect.

Highgui

This is an easy-to-use interface with simple UI capabipties. In the Java pbrary of OpenCV, the features of this module is included in two different packages namely, org.opencv.imgcodecs and org.opencv.videoio.

A Brief History of OpenCV

OpenCV was initially an Intel research initiative to advise CPU-intensive apppcations. It was officially launched in 1999.

In the year 2006, its first major version, OpenCV 1.0 was released.

In October 2009, the second major version, OpenCV 2 was released.

In August 2012, OpenCV was taken by a nonprofit organization OpenCV.org.