What is Computer Vision
There are several fields in Artificial Intelligence one such field is Computer Vision, Which is very useful to understand the Visual World. Computer Vision has been around since the 1950s. Computer Vision has become an integral part of our daily lives, and it is frequently overlooked or taken for granted. The main goal of Computer Vision is to understand the Visual Part. For suppose there are few examples which will you can able to understand about Computer Vision.
- Scanning the Bar Code for fetching the Price of a Product in the Super Market.
- Smartphone cameras identify your face and auto-focus on it, Here in the background computer vision is working.
- The technology behind Facebook's Auto suggests the face in a picture for whom to tag the photo in
- Tesla's Automated Self-Driving Cars identify the objects on the roads using Computer Vision
Computer Vision is the easiest technology to implement in your business, some real-world tasks have been worked by Computer Vision: Road Traffic Inspection (Identifying the Vehicle type, Fetching the Speed of the Vehicle), and MRI Scanning (Identifying human Body Health Status). Third Umpire Decision in Cricket Sport is also being worked by this Computer Vision.
Using Computer Vision in your Business will increase efficiency and Save Costs, Humans can do their work better and accurately. Computer Vision will be able to initiate computers to analyze the visual world, like how humans identify and process with the help of eyes.
Types of Computer Vision
There are two types of Computer Vision they are:
- Classical
- Deep Learning
1. Classical
The main focus or the goal of the Classical Computer Vision Algorithm is to detect the object and will work fast with high accuracy. The Job done by the Classical is very fast and you would really appreciate it. Classical Computer Vision had some pre-inbuilt libraries. These libraries or features will allow us to identify the object characteristics for example: the features will identify the Parts of the Human Body such as the Eyes, Ears, Nose
There are some most common libraries available for Identifying, Spoon, Fork, Cars, and Truck. The Difference between Classical and Deep Learning is In Classical there is no Neural Networks are Included but in Deep Learning Neural networks are included.
2. Deep Learning
In Deep Learning Computer Vision, Neural Networks are included. The Job done by Deep Learning would be possible only with these neural networks. These Neural Networks were also called Convolutional Neural Networks. The Convolutional Neural Networks are exposed to ample images of dogs, and cats, enabling them to autonomously identify distinctive features for each type of animal such as pointy ears for cats and fluffy ears for dogs.
These following features become a basis for the network to apply when presented with new, unseen images of dogs or cats, facilitating exact or accurate classification. Convolution Neural Networks will identify.
For most common tasks Classical Computer Vision will be able to do it with High Accuracy and will do it very fast, For More specific tasks when Classical CV doesn't provide sufficient output or the best results, Deep Learning Computer Vision Methods are the Best.
Example of How Simple it actually to innovate with Computer Vision
Let's assume you were running a Potato Chips Manufacturing Factory, You are the main Distributor for Potato Chips Whole Sale Companies. Your Job is to provide the best Quality Potato Chips Before that, you gonna pick the best quality potatoes to produce good quality Chips. For this purpose, you are requiring 3-5 people to do the job of picking up the Right and Best potatoes. But there are some drawbacks: 1. You should pay for them, 2. Human's Can Make Mistake, 3. Man Power May be Slower Than Technology, 4. Humans Can Get Sick, 5. This Job is not creative and Not Enjoyable to do.
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Solution: To overcome these drawbacks we will use Computer Vision. The Computer Vision Algorithm may have a lot of labeled images regarding Good or Best quality Potatoes and Unripe or Bad Quality Potatoes. In this work, we gonna use the Deep Learning Type of Computer Vision.
- Here we will arrange a convey belt on which the stock of potatoes is moving and 3-5 people are going to monitor and allow only good quality potatoes.
- In the middle of the convey belt, there is box-like equipment that works on the duty of knocking out rotten or bad-quality potatoes.
- When it is a Good Quality it will be allowed if it is a bad quality potato that should be knockout. Behind this equipment, Deep Learning Computer Vision Algorithm working on this task. The Algorithm will watch the work done by the workers.
This is the perfect example of how easy to implement Computer Vision in our business and it will do the work more efficiently as compared with Humans.
