1 OpenCV libraries for computer vision

From the last few decades, researchers are enthusiastic to develop machines that work and act as human beings. Computer vision (CV) is the most excellent field for researchers to fulfill their dreams. CV is a subfield of artificial intelligence. CV works with visual inputs like digital images and videos. Mainly it focuses on creating systems, which process and analyze the visual input data, to get meaningful information from those inputs. It aims to perform different types of operations on supplied visual inputs. Object classification, object identification, object tracking, edge detection, feature extraction and human identification are few applications of CV. To perform different types of operations, special algorithms with minimum computation time are required. Various libraries are developed to perform CV operations. Among all open sources, computer vision library (OpenCV) is the most popular and widely used open-source library for developing CV applications. OpenCV is designed to develop CV applications using inbuilt methods with less computational time. The major goal of OpenCV library is to provide a classy view to researchers with an optimized code mechanism on basic infrastructure. In OpenCV, optimized code is developed for a lot of applications like filters and edge detection. Using this optimal code, researchers can develop their applications. OpenCV supports various operating systems, including mobile operating systems. This chapter discusses developing computer visual applications using OpenCV. This will be useful for researchers to understand and use OpenCV for their applications.