[ Frequently Asked Question ]
Important
TA has some suggestions, since TA had tested and verified
something on somemachine, and believe they are ok.
if you have any problem and want to email to ask TA,
you should DESCRIBE THE PROBLEM MORE CLEARLY, then TA can
reproduce the error and understand what the problem you met.
(ex. which machine, what is your id and name, what command you
are executing, and the full error messages, etc)
then TA can provide his help as soon as possible if TA know what
exectly problem happened.
anyway, TA will go to classroom in course every tuesday afternoon.
so you can ask TA further questions if you can't solve them.
WARNING! Please exit the process normally after you wrote your homework!
Q:(1/24/2002)
Dear TA,
I have a question about get the value of a specific pixel.
If a image has pixels of OneByte, I can use B_PIX to get its value.
If a image has pixels of REALPIX, I can use hvGetPixel to get its value.
How can I get its value if the image has pixels of INTPIX(4Bytes)?
If there is no procedure can be used, can I use four times of B_PIX to
get a INT PIX?
If I can do so, the first pixel of INTPIX (0,0) can be got by computing
B_PIX(0,0)*2^24 + B_PIX(0,1)*2^16 + B_PIX(0,1)*2^8 + B_PIX(0,3) or
B_PIX(0,0)*2^24 + B_PIX(1,0)*2^16 + B_PIX(1,0)*2^8 + B_PIX(3,0) or
another way?
Thanks.
P
A:
Dear P,
by `man hvision`, you can see
B_PIX(I,i,j) pixel i,j of byte image I
US_PIX(I,i,j) pixel i,j of unsigned two byte image I
SS_PIX(I,i,j) pixel i,j of signed two byte image I
INT_PIX(I,i,j) pixel i,j of integer image I
R_PIX(I,i,j) pixel i,j of real image I
sincerely,
VisionTA
Q:(1/1/2002)
Dear TA:
I has a problem about HW10. What does it mean that
"choose proper thresholds" on the four types of images.
(Laplacian,minimum-variance Laplacian,Laplacian of Gaussian, and
Difference of Gaussian)
Thanks!!
A:
Dear oo,
i am not sure what does professor fuh means when he assigned hw10.
and after i saw my homework write 3 years ago, i think maybe it means,
"There are 4 methods in p.349 (all are zero-crossing)."
"Please implement 4 methods of zero-corssing to detect edge of image."
"And different method maybe needs different threshold, "
"just choose different."
maybe typo of that page, i had modified it.
and about DOG, if you want to understand what is it, you can see the
reference listed on course lecture page. if you still don't know what
is it, don't worry, hvision library had implement it. it is allowed to
use DOG by tk directly or hvDog hvision
function call.
sorry for my late reply! i am busy those days ^^;;
sincerely,
VisionTA
Q:(12/2/2001)
請問助教Gaussian noise 加到圖裡的意思是說,每一個pixel都有雜訊,
而雜訊是分佈在-255到255之間嗎???
我忘了老師那時後到底是怎麼說的,而且salt and pepper又是怎樣呢,如果
每一個pixel都有noise的話, 那整張圖一定變成黑白的了,..
我實在是不太懂題意,
所以有點不知如何下手,希望助教可以將兩個題目都解釋請楚~謝謝!
A:(1/2/2002) (sorry for so late reply ^^;;)
Dear Y,
"gaussian noise" means, there will be some noise on image, and the
noise amplitude of noise is like gaussian distribution.
(the noise "value" added to each pixel is like gaussian random variable)
the problem becomes, "what is the value added to each pixel?"
or "what is gaussian random number generater?"
if you want to see the definition of gaussian random variable,
you can see http://mathworld.wolfram.com/
(mathworld is the most famous math forum and diction on web!!)
if you still have problem, just go to R505 in CSIE building.
i will teach it if you need.
you should choose the mean (zero), st.dev. (標準差), and the amplitude
applied on the noise. you can write a program to do this.
the key point of sub-problem 2 (salt and pepper) is
you should choose the signal-to-noise ratio, not all pixel have
noise value, if noise ratio is 1/10, one of ten pixel
will have such salt-or-pepper noise, and other nine are remaining the same.
sincerely,
jsyeh@cmlab, VisionTa
ps.
below is the program header comment of my hw8 implementation 3 years ago.
hope that will help you.
i had implemented my own gaussian random variable in c.
you can find a better code of it in Knuth's famous book,
"the art of computer science" volume II. (but it is not easy to understnat
the code ^^;;)
or you can find some code on internet. (it is better to implement it ^^;;)
/************************************************************************\
hw8_1.c
This Program generate
I(nim,i,j) = I(im,i,j)+amplitude * N(0,1)
N(0,1): Gaussian random variable with zero mean and st.dev. 1
amplitude: determines signal-to-noise ratio, try 10,30
\************************************************************************/
Q:(1/4/2002)
助教抱歉,我想我用中文說明可能比較清楚,上一封我寫得不太清楚,
我不懂的是我不知道"choose proper thresholds"是什麼意思,
如何用fig.7.33 fig.7.36 fig.7.37等對影像做運算且還要選擇
適當的門檻值,還是說(我猜)課本上這三個masks並不optimal,
選擇適當的 門檻值是要我們自己製造新的masks,
再去做weighting sum的運算就好了,謝謝!!
A:
Dear r,
about "choose proper threshold", your question looks like,
"choose what threshold? change the mask? or what?"
homework#9 and homework#10 are almost the same.
in homework#9, you need to "choose proper threshold" to decide how
many pixels are edge.
let me take an example:
in hw9_1, you should "apply" roberts operator to an testing gray-level
image. so what?
lena.im --(apply_roberts_opertor)---> lena.robert
but, major issue is, how many pixels are like "edge"!
that's why we "choose proper threshold" to let lena.robert to an 0-or-1 image.
lena.robert --(choose_proper_threshold)--> lena_robert.bin
then we can said, 1 is like edge, 0 is not like edge.
***************************************************************
let's take a look of hw10_1:
we APPLY "laplacian zero-crossing mask" to an testing gray-level image.
so what?
lena.im --(apply_laplacian_mask)---> lena.lap
but, major issue is, we want to find out "edge"!
so we need to "choose proper threshold" again to convert lena.lap to a 0-or-1 image
.
lena.lap --(choose_proper_threshold)--> lena_lap.bin
then in that binary image we can said, 1 is like edge, 0 is not like edge.
so we need to "choose proper threshold" again to convert lena.lap to a 0-or-1 image
.
lena.lap --(choose_proper_threshold)--> lena_lap.bin
then in that binary image we can said, 1 is like edge, 0 is not like edge.
***************************************************************
so you didn't need to "choose proper mask", those masks all work fine!
sincerely,
jsyeh@cmlab, VisionTA
Q:(11/5/2001)
in Homework#3, how to do Hit-and-Miss operation with only one
octagon structuring element?
A:
you can prepare more structuring elements for this homework.
don't be constrained in only one structuring element(liek octagon).
it is encouraged to let your program accept different kernels
(structuring elements) for user to choose.
Q:(11/3/2001)
what kind of structuring element should we use in homework#4?
A:
in TA's own opinion, you can prepare some structuring elements
and then there will be a lot of fun.
but somebody said that Professor fuh had assigned octagon
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as the one for the first 4 binary morphological operations.
anyway, TA will not care, just go ahead. TA will appreciate who
do more experiments for different kernels.
Q:(10/13/2001)
i had emailed homework to TA, but TA didn't reply to me for
a long time. is there anything wrong?
A:
Dear p,
i really have received your homework#1,
but i didn't reply email to you because i had not checked
the correctness of your program. because there are a lot of homework
deliver to here.
so, don't worry about it.
i promise that i will verify all homework in 1 week. if you have
any problem, you can find me at TA time (every tuesday afternoon)
sincerely,
jsyeh@cmlab, VisionTA
Q:(10/13/2001)
I can't see the fomula in lecture notes. how can i see it?
(ex. in the end of chapter 3, there should be a fomula, but
i only see 144#144 145#145 ... , etc.
A:
Dear k,
about homework#3 formula, it is really in the course web page
lecture notes (chapter3)
but you will only see something like 144#144 etc. it is because
the browser didn't support the
Last updated: 4th Dec. 2001
Created: 15th Aug. 2001 by Jeng-sheng Yeh
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