Panchanand Jha

OpenCV with Python: A basic approach Panchanand Jha

Image processing is a technique to analyses and extract valuable information from an image using computer vision algorithms. Mathematically an image is nothing but two dimensional matrix and function of two coordinate x and y. The x- and y-coordinates gives location of pixel and it value. This value of pixel defines the brightness or color of an image at that location. On the other hand, image can also have three dimensional vector such as Red, Green and Blue (RGB). Therefore, it is quite important to have mathematical description of an image to develop further image processing algorithms. These algorithms have wide range of applications such as image stitching, morphing, object detections, recognition, color filtering etc. Present scenario of computer vision or digital imaging has been widely adopted in various places such as security camera, robotics vision, movies special effects and counting. The extreme use of image or video processing or one can say the major application of the image/video processing algorithms is to generate special effects on movies. In daily life we can find wide net of computer vision and it is keep on expanding. On the other hand, automobiles, aircrafts, drones, ships and trains are equipped with computer vision. Automobiles using computer vision for rear parking assistance, drones for surveillances and so on. Now a day's major use of computer vision can also be found in social network sites such as Facebook, Google, YouTube, Lens kart etc. in these sites image/video processing with facial recognition algorithm is being used. If someone upload a video on YouTube, then it has to pass through video processing algorithm for various reasons. Therefore, OpenCv plays a crucial role here for processing these images and videos. In OpenCV library multiple algorithms and function are available to perform certain task, for example any image can be resized, cropped, format, pasting or overlapping of two images, rotating, flipping, drawing, color transformations etc. can be done with simple line of code. In further chapter the details of these codes are explained. OpenCV is capable of optimizing memory handlings, error handlings, multi-threading and re-enterability. These properties of OpenCV makes it computationally efficient and best for real-time practical implementations. More details of OpenCV can be found in the OpenCV official website as this project is focused on image/video processing.