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Artificial Intelligence


                                                               Machine Learning

                                                                Deep Learning





                                                            Computer
                                                             Vision

                 Computer Vision Vs. Image Processing

                 It’s a common misconception that Computer Vision and Image Processing are the same because both deal with
                 visual data such as images and videos. However, they serve different purposes within the realm of technology and
                 Artificial Intelligence (AI).
                 Let us learn the difference between Computer Vision and Image Processing.

                                    Computer Vision                                    Image Processing
                  Computer  Vision  enables  machines  to  understand  and  Image  processing  involves  manipulating  and
                  interpret visual information, such as identifying objects,  enhancing  images  to  improve  their  quality  or
                  recognising patterns, or making decisions based on visual  extract specific features. It focuses on the technical
                  inputs. It focuses on extracting high-level information to  manipulation of raw image data.
                  mimic human vision.                                   For   example,   Rescaling   Images,   Correcting
                  For example, Object Detection, Handwriting Recognition,  Brightness, Changing Tones, Enhancing Edges, etc.
                  Facial Recognition, etc.
                  Computer  Vision  is  a  superset  of  image  processing.  Image processing is a subset of Computer Vision.
                  It  means  that  Computer  Vision  encompasses  image  It means that image processing is one component
                  processing  as  one  of  its  components  or  foundational  within  the  broader  domain  of  Computer  Vision.
                  steps, but extends beyond it to achieve higher-level tasks  Image processing provides foundational tools and
                  like recognition and decision-making.                 techniques often used in Computer Vision tasks.
                  It  operates  at  a  higher  level  of  abstraction,  focusing  It operates at a lower level, primarily working with
                  on  deriving  meaning  from  visual  inputs  and  enabling  pixel-level  data  to  transform  or  analyse  images
                  machines to perform tasks like decision-making.       without necessarily understanding their content.
                  Real-world examples                                   Real -world examples
                  •   Self-driving  cars  recognising  road  signs  and  •  Enhancing satellite images for better resolution.
                    pedestrians.                                        •  Removing red-eye effects in photos.
                  •   Augmented  Reality  (AR)  and  Virtual  Reality  (VR)   •  Converting colour images to grayscale.
                    environments.
                  •   Automated surveillance systems detecting suspicious
                    activities.


                         Applications of Computer Vision


                 Computer Vision is a technology that started in the 1970s. At that time, it was a new and exciting idea, but the
                 technology wasn’t good enough for everyone to use. People could only dream, how it could change the world.



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