Computer vision is a scientific discipline that includes methods for acquiring, processing, analyzing, and understanding real-world images in order to produce numerical or symbolic information for decision making in a useful format. It is seen as a part of artificial intelligence and machine learning and is often applied in control systems for robots. In combination with Arduino, an easy-to-use open source electronics platform, computer vision can be applied to create interesting and useful projects.
Arduino is an open source electronics platform that combines easy-to-use hardware and software. It is intended for anyone interested in creating interactive projects. The Arduino can interact with buttons, LEDs, motors, speakers, GPS, cameras, the internet and even your smartphone or your TV. This flexibility combined with the fact that the platform is open source, meaning you can copy, modify and use existing code, makes Arduino a popular tool for building electronics projects.
Computer vision with Arduino can be used for a variety of projects, from building a robot that can navigate on its own, to creating a security system that can detect motion and recognize faces. With computer vision, the Arduino can "see" the world around it, allowing it to interact in ways that wouldn't otherwise be possible.
To get started with computer vision on Arduino, you will need a compatible camera. There are several cameras available that are Arduino compatible, including the popular OV7670. This camera is capable of taking photos and recording videos, and can be easily connected to Arduino. Once you have a camera connected to your Arduino, you can start programming it to use computer vision.
At the most basic level, computer vision involves taking an image and turning that image into data that the computer can understand. This usually involves applying various algorithms to extract image features such as edges, colors, and shapes. Once these features are extracted, they can be used to make decisions. For example, if you are building a robot that can navigate itself, you can program the Arduino to move the robot forward if it "sees" a clear path ahead, and to stop or turn if it "sees" an obstacle.
One of the most interesting aspects of computer vision is the ability to recognize objects. This is done through the use of machine learning algorithms that can be trained to recognize different types of objects. For example, you could train an algorithm to recognize different types of fruit, and then use that algorithm to create a robot that can sort fruit. Or you could train an algorithm to recognize faces, and use that to create a security system that can alert you if a stranger enters your home.
In summary, computer vision is a powerful tool that, when combined with Arduino, can be used to create a wide variety of interesting and useful projects. If you are interested in electronics, robotics or machine learning, learning to use computer vision with Arduino is an excellent way to expand your skills and open up new possibilities for your projects.