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Algorithmically our red cup replacement algorithm breaks down into three main sections: cup identification, finding a suitable replacement image, and the merger of the found image into the original.  Each part presents its own technical challenges and solutions.

Identification

Our test identification algorithm is based on simple template matching.  Basically, the template image of a desired object is convolved with the original image and the correlation between the two is found at every point.  The correlation is then normalized with respect to the intensity of the original image, giving a correlation value in the range between -1 and 1.  This process is encapsulated in the matlab function normxcorr2, whith takes two grayscale image matrices and returns one correlation matrix whose width and height are the sum of the widths and heights of the original matrices.  

The program sets a threshold value (around .7 by experimentation) to determine if our template has matched a cup in the original image.  Each color channel runs and is compared with the threshold separately.  The program then ands the resulting filtered correlation matrices together so a match is only found if it matches in terms of red, green, and blue.  This prevents a red (100% red, 0% green, 0% blue) from matching with white (100% red, 100% green, 100% blue).  At this stage, all points that exceed the threshold are considered matches.  Inorder to find the actual location of the cup the algorithm finds the maximum correlation overall, records a cup at that location, and then masks out the area of the found cup.  This neutralizes the other over threshold points around corresponding to the same cup, preventing overlapping cup hits.  The algorithm then finds the next greatest maximum value and repeats until all points over threshold have been accounted.

Unfortunately, this approach only works for one size of cup in the source image (the size of the template).  To detect all cup sizes the scale of the template relative to the source image must change and the correlation must be run for each respective size.  Our algorithm scales down the original image using imresize and leaves the template small (to save on runtime by reducing the correlation size instead of increasing it).  After each small change in size the correlation function runs and saves matched regions to an accumulation array.  The function also keeps track of the masks of previous match regions so smaller cups aren’t found erroneously inside of larger cups.  The match regions are recorded at the scale of the original image, so the algorithm keeps track of the scale factor at each step and sizes the recorded region accordingly.

The search algorithm builds on the idea of template matching and expands it to a wider scope.  Ideally the program would exactly match the regions around each cup and ignore the cup itself.  Since our correlation function can not exclude the middle area, we had to use a different approach.  The replacement algorithm generates blocks around the found cup with a width proportional to the size of the cup to be replaced.  Each individual block is then correlated through the image bank (similarly to as explained above).  The main difference is that the search algorithm must consider all blocks simultaneously-- a match is only a match if it works all the way around the suspect region.  To achieve this, the correlation matrices for each block are shifted and merged by the displacement of the block from the origin of the replacement image.  This generates a correlation matrix that takes all blocks into account.  The algorithm then finds the region with the highest correlation from all the images, and passes that region to the merge algorithm.

We built our test image bank from a relatively small number of images and just used Matlab’s imread function to load each one serially.  The program runs the above block based correlation on each image, keeping track of the highest correlation value and its assosciated region.

Because of the block nature of the search algorithm, one simple improvement we made was to give the blocks different weights based on their importance to the continuity of the image.  The human eye sees lines and edges more than muted textures, so we gave more weight (by multipying their correlation matrices by a factor before the final correlation sum) to blocks that contained more edges.  This modification helped ensure that arms stayed continuous and helped with the hand problem (the frequent presence of hands over the cup).  

Combination

After finding a region to suitably replace the excised region from the original image, the new image is blended with the original.  We used a conditional blend to completely replace the red cup, and then gradually blended the surrounding buffer regions together with the original image.   Our blend algorithm used a linear intensity blend (scaled sum of the two images), but could be quickly improved with bicubic blur (taking blur information from above and below as well) and a more consistent merger (angled corners).  

Questions & Answers

find the 15th term of the geometric sequince whose first is 18 and last term of 387
Jerwin Reply
I know this work
salma
The given of f(x=x-2. then what is the value of this f(3) 5f(x+1)
virgelyn Reply
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Abhi
how do they get the third part x = (32)5/4
kinnecy Reply
can someone help me with some logarithmic and exponential equations.
Jeffrey Reply
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ninjadapaul
20/(×-6^2)
Salomon
okay, so you have 6 raised to the power of 2. what is that part of your answer
ninjadapaul
I don't understand what the A with approx sign and the boxed x mean
ninjadapaul
it think it's written 20/(X-6)^2 so it's 20 divided by X-6 squared
Salomon
I'm not sure why it wrote it the other way
Salomon
I got X =-6
Salomon
ok. so take the square root of both sides, now you have plus or minus the square root of 20= x-6
ninjadapaul
oops. ignore that.
ninjadapaul
so you not have an equal sign anywhere in the original equation?
ninjadapaul
hmm
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is it a question of log
Abhi
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salma
Commplementary angles
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Uday
hi
salma
what is a good calculator for all algebra; would a Casio fx 260 work with all algebra equations? please name the cheapest, thanks.
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a perfect square v²+2v+_
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algebra 2 Inequalities:If equation 2 = 0 it is an open set?
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or infinite solutions?
Kim
The answer is neither. The function, 2 = 0 cannot exist. Hence, the function is undefined.
Al
y=10×
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rolling four fair dice and getting an even number an all four dice
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Kristine 2*2*2=8
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Differences Between Laspeyres and Paasche Indices
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No. 7x -4y is simplified from 4x + (3y + 3x) -7y
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Need to simplify the expresin. 3/7 (x+y)-1/7 (x-1)=
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. After 3 months on a diet, Lisa had lost 12% of her original weight. She lost 21 pounds. What was Lisa's original weight?
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Cied
types of nano material
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I start with an easy one. carbon nanotubes woven into a long filament like a string
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Porter
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what is the function of carbon nanotubes?
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I'm interested in nanotube
Uday
what is nanomaterials​ and their applications of sensors.
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what is nano technology
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what is system testing?
AMJAD
preparation of nanomaterial
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Yes, Nanotechnology has a very fast field of applications and their is always something new to do with it...
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good afternoon madam
AMJAD
what is system testing
AMJAD
what is the application of nanotechnology?
Stotaw
In this morden time nanotechnology used in many field . 1-Electronics-manufacturad IC ,RAM,MRAM,solar panel etc 2-Helth and Medical-Nanomedicine,Drug Dilivery for cancer treatment etc 3- Atomobile -MEMS, Coating on car etc. and may other field for details you can check at Google
Azam
anybody can imagine what will be happen after 100 years from now in nano tech world
Prasenjit
after 100 year this will be not nanotechnology maybe this technology name will be change . maybe aftet 100 year . we work on electron lable practically about its properties and behaviour by the different instruments
Azam
name doesn't matter , whatever it will be change... I'm taking about effect on circumstances of the microscopic world
Prasenjit
how hard could it be to apply nanotechnology against viral infections such HIV or Ebola?
Damian
silver nanoparticles could handle the job?
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not now but maybe in future only AgNP maybe any other nanomaterials
Azam
Hello
Uday
I'm interested in Nanotube
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this technology will not going on for the long time , so I'm thinking about femtotechnology 10^-15
Prasenjit
can nanotechnology change the direction of the face of the world
Prasenjit Reply
At high concentrations (>0.01 M), the relation between absorptivity coefficient and absorbance is no longer linear. This is due to the electrostatic interactions between the quantum dots in close proximity. If the concentration of the solution is high, another effect that is seen is the scattering of light from the large number of quantum dots. This assumption only works at low concentrations of the analyte. Presence of stray light.
Ali Reply
the Beer law works very well for dilute solutions but fails for very high concentrations. why?
bamidele Reply
how did you get the value of 2000N.What calculations are needed to arrive at it
Smarajit Reply
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Source:  OpenStax, Red cup replacement. OpenStax CNX. Dec 19, 2011 Download for free at http://cnx.org/content/col11390/1.1
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