Computer Vision and various subcategories will have drastic changes in the future, and will surely lead to the betterment of services. Along with increased capacity, future algorithms will be easy to train on such massive data. The intervention of other technologies of the same sub-family will lead to surprising results. So let us study what is computer vision and how it works. https://www.datatobiz.com/blog/what-is-computer-vision/

1. What is
Computer Vision?

2. What is
Computer Vision?
Wikipedia Defines: “Computer vision is an
interdisciplinary field that deals with how
computers can be made to gain high-
level understanding from digital images
or videos.” Simply stating, Computer
Vision aims at enabling machines to
learn and implement the task of human
visual system. To understand how
human brain works, how it sees an object
and how it relates it to an object or past
information. To have a human
perspective.

3. HOW IT WORKS

4. Now that we have understood what Computer Vision is, let us understand how it
is actually implemented.
When a large amount of images is fed, for example pictures of a dog, the
machine will try and learn from the image. Identifying a single object, the colour
and the shape of the object, distance between multiple objects, borders for
objects and the result will accumulate a simple definition of dog for the machine.
For every next time, a picture of dog is uploaded, the machine will connect the
dots, the patterns that it learned from the training images and tell us if it is a dog
or not.
Object recognition is the basis of computer vision but also an issue. Having an
image with clearly visible objects, acceptable angle, colouring, etc. is quite
difficult. Providing unclear images to machine will lead to unexpected results.
Advanced Algorithms like Convolutional Neural Networks, Recurrent Neural
Networks, Generative Adversarial Networks, variety of Auto Encoders and many
more, are been improved and implemented on daily basis.

5. COMPUTER VISION
AND IMAGE
PROCESSING

6. These two distinct somewhere on a thin line. The process of generating new
image using an existing image is what we define as Image Processing. Multiple
filters can be added; Image can be manipulated in order to improve the
quality of image. Now this output image can be used for better understanding
of the images using computer vision. Majorly, Image Processing does not aim
to understand the content of the image while computer vision has to. Image
processing is responsible for manipulating the image in way to let the
machine identify the objects and connect the dots.
Although there are many factors contributing to improvements and ground
breaking changes in the field of Computer Vision, availability of training data
in massive amount, is primary.
Recent developments resulting in advance Neural Networks and Deep Learning
algorithms have pushed the limits, producing State-of-the-art Algorithms with
better outputs. Added computation power and point accuracy with latest
algorithms has made an impact on computer vision.

7. APPLICATIONS OF
COMPUTER VISION

8. Being a sub field of Artificial Intelligence, Computer Vision comes with and provide
solutions to high quality products. To recognize objects in a picture was good but
specifically identifying a face, along with being able to add filters is a big leap. Using Face
Detection techniques, Facebook and Snapchat detects live faces and improves the quality
of pictures with filters.
When we use google for Image Search, it simply understands the content of the image we
pass, learning the objects in the picture, it tries to match the objects and the results are
purely based content matching. When we talk about Image Classification, Convolutional
Neural Networks (CNNs) is the top pic and while other models require enough training and
inputs, CNN does it all by itself. A CNN algorithm simply takes an image as input, recognize
the objects inside and assign importance and finally compares the objects identified.
Surveillance Cameras in public places can now keep an eye on suspicious behaviour and
notify. Security features like Biometrics, Face matching and IRIS are setting new limits for
security.
Self-Driving cars are the future and various aspects of computer vision hold keys to
improve the driverless car. Medical Imaging, Optical Character Recognition, machine
inspection, 3D Model Building, Motion Detection, healthcare etc. are few of many
applications.

9. Read the full article
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https://www.datatobiz.com/blog/what-is-computer-vision/