Computer Vision is one of the demanding technologies. It uses Machine Learning algorithms to identify things. Today we are going to discuss Computer Vision's meaning, history, how it works, applications, and top tools used for it.
What is Computer Vision?
Computer Vision is a field of artificial intelligence. With the help of computer vision, computers can understand and analyze images, videos, etc. With the help of deep learning computer vision has witnessed a lot of development in analyzing different tasks that even a human takes a hard time understanding the task. Computer vision is the same as human vision but incase of computer vision computers use machine learning algorithms to see and understand things or surroundings.
History of Computer Vision
Computer Vision came into the light when scientists wanted machines to interpret visual data. It all started in 1959 when neurophysiologists experimented on a cat to recognize a group of images, the scientists found out that the cat reacted to hard edges, Image processing starts with simple shapes. In the year 1963, computers were able to transform 2-dimensional images into 3-dimensional. Due to the emergence of AI during the 1960s, people believed that with the help of AI they can take computer vision to a next level. OCR(Optical Character Recognition) which can recognize text printed in any font, and ICR( Intelligent Character Recognition) which can understand handwritten notes using neural networks.
In the year 1983, Dr. Kunihiko Fukushima has developed a network of cells that could recognize patterns. This network was known as Neocognitron. By the year 2001, facial recognition applications came into the existence. In 2010, The ImageNet dataset was made available, with this we could access millions of images of different objects. And in the year 2012, A team from the University of Toronto made CNN(Convolutional Neural Network) model called AlexNet which showed a promising error rate in image recognition.
How does a Computer Vision Work
To work with computer vision we need a lot of data to train to recognize or analyze objects. So we use CNN(Convolutional Neural Networks) to deal with huge amounts of data. For a computer or a machine to identify or analyze objects, we train them by using machine learning algorithms. These algorithms make the machines learn(identity, analyze images or objects) by themselves, rather than the developer making them identify images. With the help of CNN(Convolutional Neural Network), the image acquired is broken down into pixels and then these pixels are labeled, with the help of this we use the machine learning algorithm to recognize the images in the same way a human does.
Computer Vision Applications
Computer Vision is a growing technology. It has impacted on a lot of sectors like transportation, medical, agriculture, and many more. Now we'll look into a few applications of computer vision:-
1) Self-Driving Cars
Self Driving cars are an application of computer vision. With the help of computer vision, we can identify or detect and classify objects. Then after classification, the car can go at a certain speed ensuring the safety of passengers and pedestrians.
2) Health Care
When it comes to health care computer vision is very much helpful. We can use computer vision to scan and identify an X-ray. Using computer vision we can detect cancer, tumor, and many more. We can also monitor our health using computer vision.
3) Home Security
Using computer vision we can detect intrusion. with the help of CCTV, we can detect any intruder who is planning to enter our house, and then after detecting an intruder the owner of the house is notified about the scenario.
4) Face Filters
Nowadays people are using filters whenever they take a photo. With the help of computer vision, we can change or manipulate a person's face mostly used in face apps. This is made possible with the help of GANs [General Adversarial Network].
5) Agriculture
In Agriculture, we can use computer vision to monitor crop health and find defects or insects damaging the crops, fruits, and vegetables in the field. With the help of computer vision, we can improve the yield of the crops.
Top Tools for Computer Vision
1) OpenCV
OpenCV is an open-source library that is used for computer vision and machine learning. OpenCV was developed by Intel. OpenCV provides different functions for image detection, objection detection, and many more. OpenCV has interfaces for C++, Python, Java, etc.
2) Tensorflow
Tensorflow is also an open-source library. It is developed by Google. It can be used for training machine learning models for tasks that include facial recognition, object identification, etc. TensorFlow supports languages such as C, Python, C++, JavaScipt, Java, Go, Swift, etc.
3) MATLAB
MATLAB contains many functions for computer vision which include feature matching, object tracking, object detection, feature detection, 3D reconstruction, camera calibration in 3-D, etc. The MATLAB toolbox algorithms support code generation in C++ and C.