Page 320 - AI Ver 3.0 class 10_Flipbook
P. 320

For example, in the given, if we split the image into
              three  different  channels,  namely  Red  (R),  Green                    R
              {G)  and  Blue  (B),  the  individual  layers  will  have
              the following intensity of colours of the individual
              pixels.  These  individual  layers  when  stored  in  the
              memory looks like the image on the extreme right                         G
              i.e. grayscale image because each pixel has a value
              intensity  of  0  to  255  and  as  studied  earlier,  0  is
              considered as black or no presence of colour and
              255 means white or full presence of colour. These
              three  individual  RGB  values  when  combined  form                     B
              the colour of each pixel.
              Additionally, understanding these individual layers is critical for various image processing tasks, such as colour
              correction,  filtering,  or  transformations,  where  manipulating  the  intensity  values  of  specific  channels  can
              significantly alter the overall appearance of the image. Each pixel in an RGB image, therefore, is not a single value
              but a combination of three values that together define its complete colour.



                            Task                                                               21 st  Century   #Creativity
                                                                                                   Skills



                Go to the following link www.piskelapp.com and create your own pixel art. Try and make a GIF using
                the online app for your own pixel art.


                                                                                          21 st  Century   #Media Literacy
                                                                                              Skills
                         Video Session

                   Watch the video on "How Computer Vision Applications Work? " at the given                                                                                             Exercise
                   link:
                   https://www.youtube.com/watch?v=oGvHtpJMO3M or scan the QR code and answer the                                                                                    Solved Questions
                   following question:
                   What do you understand by CNN?                                                                                                                            SECTION A (Objective Type Questions)
                                                                                                                                                   uiz
                                                                                                                                            A.  Tick ( ) the correct option.

                                                                                                                                                1.  What is the purpose of facial recognition in smart homes?
                                                                                                                                                  a.  To increase Internet speed
                                                                                                                                                  b.  To recognise family members for security purposes
                       Convolutions                                                                                                               c.  To generate digital filters
                                                                                                                                                  d.  To track weather changes
              Convolutions are mathematical operations used in signal processing and deep learning to filter data. In neural
                                                                                                                                                2.  What is the primary goal of Computer Vision?
              networks, they involve applying a filter or kernel over input data (like an image) to detect features such as edges or
              textures. The output is a transformed version of the data, emphasising relevant features for tasks like classification              a.  To understand and interpret visual information from the world
              or detection.                                                                                                                       b.  To simulate human brain activity
              We can create our own convolutions. The way to create the same has been explained in next chapter with the help                     c.  To create 3D models from images
              of http://setosa.io/ev/image-kernels/ link.                                                                                         d.  To develop algorithms for natural language processing


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