Computer Vision and Image Processing: Fundamentals and Applications

In this article, I will discuss some fundamental concepts of computer vision and image processing and finally I will highlight some important applications of computer vision.

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What is computer vision?

computer vision is the field of computer science the objective is to build a machine so that it can process and interpret images and the videos just like human visual system does. so, I can say it may be complement of biological vision.

 Computer vision is a field of computer science that works on enabling computers to see, identify and process images in the same way that human vision does and then provide appropriate output

 

Similarity between Human Vision and Computer Vision

The first block represents the human visual system. In the case of the human visual system, we use our eyes to perceive objects, images, or videos. Following this, the brain processes the information and makes intelligent decisions based on it. Similarly, in a computer vision system, cameras are used for image and video acquisition, which may involve a single camera or multiple cameras. After acquisition, preprocessing is performed, referred to as image processing. Subsequently, pattern recognition and artificial intelligence algorithms are applied for decision-making.

Image Processing vs Computer Graphics

There is a noticeable similarity between human visual system and the computer vision system. In the case of the human eye, light photons are converted into electrical signals, and in the case of a camera, light photons are similarly converted into electrical signals. This demonstrates the resemblance between these two systems. 

Now, I would like to emphasize the distinctions among computer vision, image processing, computer graphics. 

In computer vision, input consists of images or videos, and the output is their interpretation, such as the analysis of images or videos. 

In image processing, the input is an image, and the output is also an image. For example, if one needs to enhance the visual quality of an image, image processing is applied, where both input and output are images. Another example is noise removal from an image, which also involves image processing with an image as input and output. 

In computer graphics, the input is a scene or model, and the task involves generating an image from the model. 

Computer Vision vs Image Processing vs Computer Graphics

• Computer Vision
• Input: Image                          Output: Interpretation
• Image analysis, Image Interpretation, Scene Understanding.
• Image Processing
• Input: Image                          Output: Image
• Image recovery, reconstruction, filtering, compression, visualization.
• Computer Graphics
• Input: Scene representation   Output: Image

Computer Vision Applications

Now, let us explore the applications of computer vision. There are numerous applications of computer vision, such as in multimedia, video surveillance, image analysis, musical image interpretation, 3D, image segmentation, human-computer interactions, 3D object recognition, optical character recognition, augmented reality, inspection of components, and automation. The applications of computer vision are vast and diverse.