How does a computer read an image?
Computers don’t “see” images in the way humans do. Instead, they interpret images as arrays of numerical values. The basic process of how a computer reads and processes an image are:
- Pixel Values: An image is made up of pixels, which are the smallest units of information in an image. Each pixel has a value that represents its color and intensity. In the case of an RGB image, there are three values for each pixel corresponding to the Red, Green, and Blue channels.
- Digital Representation: The RGB values are usually represented as integers ranging from 0 to 255. 0 represents the absence of color (black), and 255 represents the maximum intensity of that color (full brightness).
- Image Matrix: The computer reads the image as a matrix of numbers, where each element in the matrix corresponds to the pixel value at that location. For a color image, there are typically three matrices, one for each RGB channel.
- Image Processing: Image processing algorithms are applied to manipulate these numerical representations. Common operations include resizing, cropping, filtering, and more.
What is OpenCV Library?
OpenCV, short for Open Source Computer Vision Library, is an open-source computer vision and machine learning software library. Originally developed by Intel, it is now maintained by a community of developers under the OpenCV Foundation.
In this article, we delve into OpenCV, exploring its functionalities, applications, and practical examples.