There is a mistake at 8:45 . The highest value we get is at different point. And what if there is a bright portion of image? Then we will get more value than the value of kernel position. Please clarify my question. and the position i was talking about in the image is (8,5). Please check.
I will check it out at 8:45, even if all pixels are bright it will match with the same portion in the image. Because we multiplying image pixels with mask
In first example you have not added 0 padding and 2nd example you have added 0 all side .. so when to add and not to add plz tell ma'am ... I have exam tomorrow 😭
Whether to add or not completely depends on size of image and application. If size of image is small it should be added. In exam sometime they ask to do with zero padding. If not asked you can state that you are using zero padding
Nice concept and very easy for understanding.
Thank you so much 😊
if the sum of products is more than 255 in many cases or all case what happens?
It will not happen in all cases. Sum is highest where template matches
@@TheVertex-Engg-Lectures
What if the other part having all 9's, then won't it be greater than that part?
@@TheVertex-Engg-Lectures We use Sum of Squared difference or Normalized Cross-correlation? isn't it?
@@muhammadiqbalbazmi9275 no
There is a mistake at 8:45 . The highest value we get is at different point.
And what if there is a bright portion of image? Then we will get more value than the value of kernel position.
Please clarify my question.
and the position i was talking about in the image is (8,5). Please check.
I will check it out at 8:45, even if all pixels are bright it will match with the same portion in the image. Because we multiplying image pixels with mask
@@TheVertex-Engg-Lectures So, it is like where we are getting the same value as of the kernel will be the match, not the maximum value?
@@monesseikh1225 yes absolutely right 👍
10:17 kya 0 padding krne se ya na krne se answer mei koi fark padega??? For both correlation and convolution..
Take sample image and try doing with and without padding and verify your answers
ma'am spatial filtering ( complete topic) needed. plz.....
this is only portion of this topic.
Which university you belong to and
What are the topics?
@@TheVertex-Engg-Lectures Rajasthan Technical University, Kota
Topics: smoothing spatial filter, sharpening spatial filter, 2D DFT,. And Frequency Domain filters
@@akshaykumargurjar8743 smoothing and sharpening already uploaded.
DFT will be uploaded soon
@@TheVertex-Engg-Lectures plz upload DFT ASAP, my internals are ongoing
@@TheVertex-Engg-Lectures Got it.....and Now cleared. Thanks
In first example you have not added 0 padding and 2nd example you have added 0 all side .. so when to add and not to add plz tell ma'am ... I have exam tomorrow 😭
Whether to add or not completely depends on size of image and application. If size of image is small it should be added. In exam sometime they ask to do with zero padding. If not asked you can state that you are using zero padding
@@TheVertex-Engg-Lectures Thanks ♥️ You Earned A Subscriber 💯
@@hardikkurdikar5872 😊 keep learning 👍