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Hi'
Do you have basic idea of fuzzy logic?
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Oh yes we know about fuzzy rule,membership function,fuzzification ,defuzzification and all...but how it is applied to this project?what are fuzzy filters..
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raisaldanha
hey everyone!!!
My group has selected 'NOISE REDUCTION IN IMAGES USING FUZZY LOGIC' as our BE project but we do not know much about it.It is based on some implementation of fuzzy filters and we have taken this from an ieee paper.We are really interested in it but have no idea about it😕 .It would be really great if anyone could help us or tell us the logic behind this .And by the way is this a BE level project?
I guess it is done using MATLAB..
Please help it is really urgent.....
Can you provide any specific material from the paper, or at least name it? If not, you might try using a fuzzy rule base to adjust the amount of smoothing provided by a conventional filter. For instance, one solution is to perform a weighted averaging of the original image and a highly smoothed image, with the weighting being determined locally by a fuzzy rule base. In places where there is noise, as opposed to an edge, the smoothing could be turned up by the fuzzy rules.
-Will Dwinnell
<a href="https://matlabdatamining.blogspot.com/" target="_blank" rel="nofollow noopener noreferrer">Data Mining in MATLAB</a>
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filtering noise using fuzzy logic is by implementing fuzzy filters.
1) The fuzzy filter computes “fuzzy derivative” in order to be less sensitive to local variations due to image structures such as edges
2) The fuzzy membership functions are adapted accordingly to the noise level to perform “fuzzy smoothing”.
The general idea behind the smooth filter is to average a pixel using other pixel values from its neighborhood, but simultaneously to take care of important image structures such as edges. The filtering involves reduction of noise while preserving or enhancing edges.
Consider a 3*3 neighborhood of a pixel (x, y). A simple derivative at the central pixel position (x, y) value in the direction D (D=NW, W, SW, S, SE, E, NE, N) is defined as the difference between the value of the central pixel (x; y) and its neighbor pixel in that direction D. This derivative value is denoted by Ñd (x; y).
For example, Ñn (x, y) = I(x, y-1)-I(x, y)
The principle of the fuzzy derivative is based on the following observation. Consider an edge passing through the neighborhood of a pixel (x, y) in the direction SW, NE. The derivative value Ñnw (x, y) will be large, but also derivative values of neighboring pixels perpendicular to the edge’s direction can expected to be large. For example, in NW - direction we can calculate the derivative values Ñnw (x, y), Ñnw (x-1, y+1) and Ñnw (x + 1; y- 1).. The idea is to cancel out the effect of one derivative value which turns out to be high due to noise. Therefore, if two out of three derivative values are small, it is safe to assume that no edge is present in the considered direction. This observation will be taken into account when we formulate the fuzzy rule to calculate the fuzzy derivative.
NW: (if Ñnw(x,y) is small and Ñnw(x-1,y+1) is small) or (if Ñnw(x,y) is small and Ñnw(x+1,y-1) small) or (if Ñnw(x-1,y+1) is small or Ñnw(x+1,y-1) is small thenÑnwf(x,y) is small
Fuzzy smoothing:
The fuzzy filtering of the image reduces noise components of pixels by means of correction of pixel values. We describe this in terms of a correction term D. To compute correction term D for the processed pixel value, we use a pair of fuzzy rules for each direction. The idea behind the rules is if no edge is assumed to be present in a certain direction the derivative value in that direction can and will be used to calculate the correction term. Edge assumption part can be realized by using the fuzzy derivative value, for filtering part we will have to distinguish between positive and negative values.
Fuzzy rules to calculate positive and negative values are
NW = lnw(+):if Ñnwf(x,y) is small and Ñnw(x,y) is positive then D positive
lnw(-) :if Ñnwf(x,y) is small and Ñnw(x,y) is negative then D negative
We are interested in obtaining a correction term D, which can be added to the pixel value of location (x, y). Therefore, the truthness of the rules ld(+) and ld(-) are aggregated and rescaled. So, each direction contributes to the correction term D.
The fuzzy rules for smoothing are as follows:
If a pixel is darker than neighbouring pixels then make it brighter
If a pixel is brighter than neighbouring pixels then make it darker
Else leave it unchanged
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#-Link-Snipped-#
this is the ieee paper that we r trying to impement
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can anyone tell me the different types of noise that affects IMAGES and how do they create a difference ...like salt and pepper produces black and white spots in an image.....like this...
plz pls somebody atleast reply to this......hv got few types as follows
erlang,rayleigh,multiplicative,periodic,poisson.....but dun noe its characteristics and how it affects images.....pls reply.....
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May I request you not to use SMS text in your posts? Play proper attention to text formatting.
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ok sorry for that i would appreciate if you could help me with my problem instead of checking the text formatting.
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Hai this is chaithu
My final BE project is also this one only and i have completed it very successfully.
Anyone need any kind of help am always der to help😎
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Hey Thanks a lot, after a very long time someone has finally replied to this post.
did you do this project in MATLAB?
could you tell me after finding the basic derivatives, how you have used the basic and related gradients to find the fuzzy derivative?
and how have you implemented the fuzzy rules.
thanks a lot.
please could you reply as soon as possible.
My email id is <email removed>#-Link-Snipped-#
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Hi Chaithu,
I'm Mamahuu,
I'm doing the project on noise detection and reduction in image using fuzzy logic, the problem is that I can't write MATLAB program for this project.
Would you please send me your program it will be my starting point.
thanks
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Hi Chaithu..
.well i have got the project but i need your help please there are some stuff which I dont understand.
waiting for your reply
thanx in advance.. 😀
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Hi Chaithu, i m Aatish doing BE in Computers.
I'm doing the project on noise detection and reduction in image using fuzzy logic, the problem is that
i m new to the MATLAB language and i can't able to write the code in matlab for my project.
Would you please send me your program it will provide gr8 help to me.
here is my id:- <removed>
thanks
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CE guys plz help me. i have only learned the basics of matlab,how i start with my project.....
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I guess no one will do your homework. The best thing to do is to share whatever code you've written on your own and seek help from others.
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hi the The_Big_K, could u plz tell me how i learn the matlab since in market there r no such good book r available.Could u tell my wat should i refer so that i can understand the matlab and its features.
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Chaithanya143
Hai this is chaithu
My final BE project is also this one only and i have completed it very successfully.
Anyone need any kind of help am always der to help😎
Dear Chaithanya,
Would you please publish MATLAB code for this project.
Thanks & Regards,
Sanjay Kumar
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@Sanjay Kumar: Sharing your email ID in a public forum isn't a good idea. Rather, ask the members to share the code here so that everyone benefits.
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can u plz send me the matlab code for noise reduction in images using fuzzy systems really its urgent
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hi tis s ramya can u plz get d code for noise reduction in images using fuzzy logic
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