Entering into the world of Computer Vision
Computer vision is the field of computer science that focuses on replicating parts of the complexity of the human vision system and enabling computers to identify and process objects in images and videos in the same way that humans do.
➡Until recently, computer vision only worked in a limited capacity.
⭐Computer vision is the fastest growing technology in the field of Artificial Intelligence. To better understand the concepts in Computer Vision having in-depth knowledge of basic image/ video processing algorithms is very important.
One of the driving factors behind the growth of computer vision is the amount of data we generate on a daily basis that is being used to train and make computer vision better.
According to markets’ reports, the computer vision market is expected to rise by 💲17.4 billion by 2024! Vision-based robotic system and application-specific computer vision systems are transforming the workplace through its emerging technologies.
Venturing into the History of Computer Vision-
Computer scientists first started thinking about vision about 50 years ago.
In 1966, MIT professor Seymour Papert gave a group of students an assignment to attach a camera to a computer and describe what it saw, dividing images into “likely objects, likely background areas, and chaos.” Clearly, this was more than a summer project, as we are still working on it half a century later, but it laid the groundwork for what would become one of the fastest-growing and most exciting areas of computer science.
Computer Vision is one of the most exciting fields in Machine Learning and AI. It has profound applications in many walks such as self-driving cars, robotics, augmented reality, face detection in law enforcement agencies.
OpenCV is an Image Processing library created by Intel and maintained by Willow Garage. Available for C, C++, and Python, OpenCV is Open Source and free.
Applications of Computer Vision-
By integrating computer systems with Computer Vision technology, computers will be able to extract, analyze and understand useful information by processing any number of images. Simply, Computer Vision delivers computers or machines with human-like abilities to see, identify and process images.
Isn’t that amazing?
Though the concept of Computer Vision sounds quite simple, technically speaking, it is the actual process behind making computers able to recognize images of different objects is very complex.
While computer vision (CV) has not reached parity with human ability, its uses are already widespread, and some may be surprising. Scanning a barcode, the yellow first-down line while watching football, camera stabilization, tagging friends on Facebook, Snapchat filters, and Google Street View are all common uses of CV.
Computer Vision Tasks-
Computer Vision, mainly OpenCV itself can do wonders! From changing the color of an image from RGB to BGR or B/W, changing hue saturation values essential in gesture recognition and facial identification, to increasing the sharpness of an image by adjusting binary threshold and rescaling features, rotating image to name a few.
OpenCV is most used for tasks like
*Image classification into say, cats and dogs, horses and humans, rock or paper or scissors
*Object Identification, like your computer identifying “Oh this is a cat and not a dog” coz of its pointy ears and short tail
*Object Detection and Recognition
*Object Segmentation, like your computer detecting “Oh wait, this image pixel belongs to the dog’s tail”
* Video motion analysis useful in Pose estimation in Microsoft Kinetics while you play your Xbox, Scene reconstruction in industries and forensics and Image restoration.
:: Computer Vision and Human-Computer Interaction (HCI) enable humans to interface with the machine in non-invasive ways.
