The Goal Of Computer Vision is An Exciting area That Are Combines Computer Science, AI , And Neuroscience That Aims is to Make Machine That Can Understand And Interpret And Understand the Visual World. We Know Computer Vision is Quickly Changing Our Everyday Lives and Businesses. it is Also Identifying or recognize face in photos And Also Help For Self Driving Car. This Blog Gives a Complete Top To Bottom Easy Understand Overview Computer Vision Including its Background , Basic Idea , Keys , Fundamental Concept And Most Important Technology.
What Is Computer Vision?
Computer Vision It is A Branch Of AI, its Aims to Provided Computers the Ability to see Understand, and Act upon Visual information. Information from photos and videos can be automatically extracted, analysed, and understood in this way. Essentially Computer Vision Allows Computer to See , interpret, And Analyse Visual Data In a Way That is Comparable to Human Vision , But With Significantly High Speed And Precision.
Computer Vision Take can range from basic image Processing Like filtering and Enhancing to Advanced Application like Object Detection , Image Segmentation, Facial Recognition And 3D Scene reconstruction cover at all. Then Main Goal to train Computer algorithm Decision making And perceive visual stimuli much Like A Person.
History Of Computer Vision
In the 1950s and 1960s, When AI was Just Starting to take off. In the beginning, studies focused primarily with deducing the fundamentals of visual processing from the way people’s eyes work. Lets Take a Look A Few Important turning points in the History of Computer Vision :
The Early Days : 1960s – 1970s
1960s : one Subfield of AI that Has recently Grown In Prominence is Computer Vision. It As A Branch of Artificial Intelligence. Drawing inspiration from the human visual system, early research centred on basic image processing tasks like object recognition and edge detection.
1970s : The mathematical underpinnings of pattern recognition and image processing became better understood in the 1970s. Algorithms for edge, corner, and shape detection were created by researchers, setting the stage for future developments in computer vision.
The Rise Of Machine Learning :1980s -1990s
1980s : The Introduced of Machine Learning in This Area of Computer Vision like Neural Networks, gave it a new lease on life. Scientists Started to look into Ways to tech computers to see a recognize pattern and also Details In Image.
1990s : These Model Led the Way for Deep Learning Method used in A Computer Vision Today. Image Recognition and Object Detection Made Big Steps Forward thanks To Also Creation Of Complex Algorithm And Computer Model As Like Support Vector Machines(SVM) And Convolutional Neural Network.
Revolution in Deep Learning: 2000s–Now
2000s :Researchers were able to train deep neural networks on vast amounts of data thanks to the availability of large datasets like ImageNet and the emergence of powerful GPUs. This resulted in significant advancements in several computer vision tasks, including picture classification and object detection.
2010s-Present: Technological advancements in generative models, deep learning, and transfer learning have propelled computer vision to new heights of development and invention. Computer vision has many modern-day uses, including in medicine, autonomous vehicles, shopping, and the entertainment industry.
Fundamental Concept in Computer Vision:
Understand the Basic of Computer vision, First You Need to Know About some basic ideas like How to Process Images, Find Features, And recognize Pattern. lets Talk About These Ideas In More Topic In Depth :
Image Processing :
Computer Vision image Processing is The Process of Changing and Analysing Image to gets useful Information from Them. Image Processing Techniques There Are Two Main Type
- Low Level Image Processing : Main Goal Of Low-level Image Processing is To Make Better Image or Pure Better Simple Things Like lines And textures. This Type Image Process does Simple Things to Image , Like Removing Noise and Improving Them.
- High Level Image Processing : This type of image processing includes more complicated tasks like object identification, picture recognition, and image segmentation. High-level image processing tries to figure out what a picture is about by finding objects, patterns, and connections in the visual data.
Common Image Processing Technique :