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here's the general algorithm, in pseudo-code:
startpoint = start point of fill
startcolor = color of pixel at startpoint
fill(startpoint, fillcolor, startcolor);
fill(point p, color fillcolor, color startcolor)
{
if (p.color != startcolor)
{
p.color = fillcolor;
fill(point(p.x+1, p.y), fillcolor, startcolor);
fill(point(p.x+1, p.y+1), fillcolor, startcolor);
fill(point(p.x-1, p.y), fillcolor, startcolor);
fill(point(p.x-1, p.y-1), fillcolor, startcolor);
}
}
pro-tip:
this is recursive, which can be a problem for large fills. but you can eliminate the recursion using a stack.
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What specific information are you looking for?
"The clue train passed his station without stopping." - John Simmons / outlaw programmer
"Real programmers just throw a bunch of 1s and 0s at the computer to see what sticks" - Pete O'Hanlon
"Not only do you continue to babble nonsense, you can't even correctly remember the nonsense you babbled just minutes ago." - Rob Graham
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any kinds of algorhitms.
i know a*, i just want to know others, maybe find something i like.
For games, AI, whatever![Rose | [Rose]](https://codeproject.global.ssl.fastly.net/script/Forums/Images/rose.gif)
nelsonpaixao@yahoo.com.br
trying to help & get help
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I want an array of colors which can be distinguished eaily by human.
The more colors the better.
At least, manually constructed array is also ok.
Thanks very much.
system
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You want to choose red, green, and blue levels as points in a three-dimensional space that are as far apart as possible. This space is a 3D array where each index goes from 0 to 255.
There is also a perceptual component to this problem; a person's perception of color levels is not linear with respect to the numeric indexes. For example, changing from red 20 to red 30 may be perceived as a much different increment than changing from red 120 to red 130.
So one approach is to use the geometric approach to suggest colors that are different, present them to the user, and allow the user to select the colors that are used. An enhancement would be to allow the user to "edit" the color presented to increase the difference to the colors already selected.
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In image processing, high contrast colors are often used to display labeled images. That is, image that has gone thru the labeling/connected component process. In that case, to display the resultant image, we use something called "Binary Color Table", which consists of 15 different colors, that are completely different with each other.
These are the colors;
byte bSize = 15; // Binary palette has 15 colors, cycled 15 times.
byte r[] = {255,0,0,255,255,0,255,255,127,127,0,0,255,127,127};
byte g[] = {0,255,0,255,0,255,127,0,255,0,127,255,127,255,127};
byte b[] = {0,0,255,0,255,255,0,127,0,255,255,127,127,127,255};
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Take a look also here[^], there are also the text tables for each array.
Russell
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I am very worried about a man in the middle attack on my public key cryptography and want to set up a shared key logon. I want the client to have individual shared keys to reduce the likelyhood of a known plaintext/ciphertext attack. I would also really like to set up key distribution so each user recieves a new key for each session and when the session is closed the client recieves a new key to log on. I want this to be like an ssl logon seesion except that I want the entire website encrypted. Could someone please post any good references for a shared key logon or some code,please?
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A general suggestion: Depending on a single cipher, no matter how good, is brittle. Using multiple cipher layers makes your code exponentially harder to decrypt.
BTW, how are you distributing keys? If the man in the middle is intercepting communications, he'd also get the new keys.
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I've just finished writing a utility to migrate data from optical libraries to a NAS box and now I'm trying to come up with a formula to estimate the time of completion given the following data:
1) Total amount of data
2) No: of drives in library
3) Average read speed of the drives
4) Total no: of files
5) Fixed overhead for each file
6) Average write speed of the NAS box (this also takes into account the network write speed)
The formula that I am using now looks like this:
(Total data / (No: of drives * Average read speed)) + (Total files * Fixed overhead) + (Total data/ Average write speed)
I don't think this right in all cases. The utility launches 1 thread for each drive in the library. So there is some parallelisation of the copy process. But I think the above formula would only work if the copying is done in a sequential manner.
Does anyone have a better idea on how to do this by taking into account that the reads and writes happen in parallel?
Please note that in the program itself, I just use the no: of files processed so far and the time taken to process them to guesstimate the time remaining. This formula is to create an excel file where the user can enter the data given above and get an approximate time of completion before actually starting the migration.
Any help is greatly appreciated.
The user formerly known as pkam.
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I think the gating factor is the slower of reading, writing, or data transfer rate. It doesn't matter how fast you can read the data if writing slower. If reading can't keep up with writing, then reading is the limiting process. Of course, this analysis is based on aggregate rates which may be hard to judge but it seems you have some average values to work with.
If you don't have the data, you're just another a**hole with an opinion.
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Thank you for taking the time to respond to my question, Tim.
The user formerly known as pkam.
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There are complexities and interactions you can't anticipate, so a more reliable approach is to make completion-time measurements for different parameter combinations.
Looking at the graphs of times for different values of a single parameter will give you insight as to how it really affects completion time.
Multiple regression will give you formulas that estimate completion time based on the values of multiple parameters.
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Thank you for your response Alan. I just needed a rough estimate. So for now I'm using the method suggested by Tim. Also the utility has currently been tested only on a small test configuration. When we do further testing, I'll try out your method.
The user formerly known as pkam.
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Hi, can somebody tell me how do i get the equation of a spline thru n points.In my problem, i had 3d points scattered all over the space, i projected them on a plane.I am supposed to join these points and create a spline using c/c++ program.Can anyone help me out in this.Plse do et me know.Thnx in advance.
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Does your homework problem specify a particular type of spline? There are lots.
If you don't have the data, you're just another a**hole with an opinion.
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My task was actually to develop a program which would generate a curve to connect a set of points scattered all over the space and for that i wanted to create a cubic spline.Anyways, thnx for ur very humble reply.
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The standard approach to a 3D spline is to treat the X, Y, and Z coordinates separately, and do three 2D splines. I.e. do a spline for all the X's vs. their time index (0, 1, 2, 3...), then the Y's and Z's.
To interpolate for a fractional time index, you get the X, Y, and Z coordinates independently from the three corresponding 2D splines.
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Thnk you very much for the reply. 
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Hi,
I'm trying to create a program that guesses the next colour the user will select, based on previous selections. I've come across Markov Chains, and this seems like the tool I need. However, after reading a lot on the theory, I'm having difficulty in implementing it (I'm using C#). Basically, I have five colours. (Red, Green, Blue, Yellow, Black). The user selects a colour, then another one and so on. After N amount of colours chosen, the user selects "predict". I want the program to then guess what the next colour would most likely be based on the previous selections. How do I calculate the values of the transition matrix each time the user selects a colour? And how do I allow the program 'learn' that the user likes a particular order?
Thanks for any help
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Your assumption that there's a pattern to the user's selections may not be correct.
You can store the total number of times the user selected each color. The highest number would be the user's favorite color selection.
You could also have an N-by-N matrix representing two consecutive color selections. (The X coordinate is the ith selection, and the Y coordinate is the (i+1)th selection.) The number at each (X, Y) pair is the number of times this sequence was chosen. Thus for any selection, X, you could see what the most common following color, Y, was, and use that for your prediction.
Likewise, this could be extended beyond the 2-dimensional case to tabulate longer sequences.
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Hi,
Thanks for the reply! The method you suggested was the one I originally tried, but I'm sure how efficient it would be if, instead of a few colours, I use 5000 as the matrix would be huge. Could you suggest a more efficient method for large scale predicitons? I heard neural networks might work, but I'm not sure which method would be the best.
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It's difficult to use a neural net with non-numeric data, e.g. colors. But you could use a neural net with the colors' red, green, and blue components, which ARE numeric.
So you'd have three input neurons for each previous color, e.g. for two previous colors you'd have r0, g0, b0, r1, g1, b1. There would be either three output neurons for the RGB components of the predicted color, or you could have three separate neural nets for the three outputs, each with a single output neuron. (The inputs would be the same for all three nets.)
You should have at least one, and possibly several middle layers.
The training set would have RGB components for the previous colors, and the actual selected color's RGB values, which you'd subtract from the predicted color's RGB values to generate error terms for back-propagation.
(This is all assuming there's a pattern to the user's selections, which hasn't been established.)
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