How can I distinguish two images having coordinate of object? - c++

I am using OpenCV with c++ and I have several images with located minutiae (end/branch).
Minutiae have:coordinate(x,y) , type(end/branch) and angle.
How can distinguish one image from another having this information??
I need very simple algorithm or code or any idea!!!
Example with located points:
http://ifotos.pl/zobacz/minucjepn_xhaqnwh.png/
How can I distinguish images with thats located points??

Have a look at geometric hashing.

#user1666649, this is not as simple as you told. If you look for scientific articles, there are many of Bologne University about this. If you need a semple code you can look for NBIS from NIST/FBI. However if you are looking a good algorithm, you will need to buy a commercial one from Veridis, Neurotechnology, Aware, etc...

Related

Detour recast tileLayer what is it about

I would like to ask how tileLayers in detour work.
Can i layer any 2 tiles resulting in "cuts" being merged into bigger holes and in what manner, are there any limitations? How many of these layers can i have and how they interact when navigating. Can i have for example basic always unchanged layer with whole map and then multiple layers with user placed geometry etc...
I'am talking about dtNavMeshCreateParams::tileLayer from original lib. There is some implementation using it in TempObstackes example. But it is not well explained (it has many custom things inside but i'am interested only in function of those layers)
Thank you in advance, i cant find much info about this online so any help would really be appreceated.
So actually i finally (many hours) found my answer to what these layers are used for:
http://digestingduck.blogspot.com/2011/02/heightfield-layer-portals.html
(btw this seems to be blog of navmesh lib author, enjoy)

What is the way to implement neural networks in c/c++?

I wanted to use neural networks for pattern matching in c++. The scenario is like this:
The main goal is to determine a product by name when captured by a camera.
A rectangular pack of a product (say for example the container of a toothpaste product) is cut into its edge so that the all of its side are shown in one plane. The camera takes a picture of the pack and compare its patterns to the database.
If the patterns are found from the search, then display the name of the product.
Else, store the patterns of the product to the database with its name (say the brand of the toothpaste).
What I mean by pattern is the distinct feature of the product pack among the other products.
I want to know the following using c/c++ (linux, windows, or mac os doesn't matter):
Is there a library that makes work somehow easier?
If a library is not available, what is the best algorithm you can suggest for pattern matching?
I think first, you will need to do some post processing on picture captured by a camera to normalize it (size, angle, ...) For that job, you can use OpenCV.
Then if you want to setup a NN, maybe you should give a try to FANN (Fast Artificial Neural Network) http://leenissen.dk/fann/wp/
The library is compatible with Linux/Windows and really easy to use!

Best approach for doing full-text search with list-of-integers documents

I'm working on a C++/Qt image retrieval system based on similarity that works as follows (I'll try to avoid irrelevant or off-topic details):
I take a collection of images and build an index from them using OpenCV functions. After that, for each image, I get a list of integer values representing important "classes" that each image belongs to. The more integers two images have in common, the more similar they are believed to be.
So, when I want to query the system, I just have to compute the list of integers representing the query image, perform a full-text search (or similar) and retrieve the X most similar images.
My question is, what's the best approach to permorm such a search?
I've heard about Lucene, Lemur and other indexing methods, but I don't know if this kind of full-text searchs are the best way, given the domain is reduced (only integers instead of words).
I'd like to know about the alternatives in terms of efficiency, accuracy or C++ friendliness.
Thanks!
It sounds to me like you have a vectorspace model, so Lucene or a similar product may work well for you. In general, an inverted-index model will be good if:
You don't know the number of classes in advance
There are a lot of classes relative to the number of images
If your problem doesn't fit these criteria, a normal relational DB might work better, as Thomas suggested. If it meets #1 but not #2, you could investigate one of the "column oriented" non-relational databases. I'm not familiar enough with these to tell you how well they would work, but my intuition is that you'll need to replicate a lot of the functionality in an IR toolkit yourself.
Lucene is written in Java and I don't know of any C++ ports. Solr exposes Lucene as a web service, so it's easy enough to access it that way from whatever language you choose.
I don't know much about Lemur, but it looks like it has a similar vectorspace model, and it's written in C++, so that might be easier for you to use.
You can take a look at Lucene for image retrieval (LIRE) here: http://www.semanticmetadata.net/2006/05/19/lire-lucene-image-retrieval-04-released/
If I'm mistaken, you are trying to implement a typical bag of words image retrieval am I correct? If so you are probably trying to build an inverted file index. Lucene on its own is not suitable as you probably have already realized as it index text instead of numbers. Using its classes for querying the index would also be a problem as it is not designed to "parse" (i.e. detect keypoints, extract descriptors then vector-quantize them) image into the query vector.
LIRE on the other hand have been modified to index feature vectors. However, it does not appear to work out of the box for bag of words model. Also, I think I've read on the author's website that it currently uses brute force matching rather than the inverted file index to retrieve the images but I would expect it to be easier to extend than Lucene itself for your purposes.
Hope this helps.

Graph-Drawing / TSP-Route-Drawing in C++ with "known" coordinates: How? Which Library/Tool?

i'm developing some kind of heuristics for a variation of the vehicle-routing-problem in C++.
After generating a solution, i want to plot this solution. The solution is a composite of various tours, all starting and ending at a common depot.
Therefore i have a vertex-set with all the coordinates and edges defined by two vertex-id's each. Furthermore i have all the distances between vertex-pairs of course.
It would be helpful to plot this in an extra-window opening in my program, but writing a plot to a graphics-file should be okay too.
What is an easy way to plot this? How would you tackle this?
First i tried to look for common graph-visualization packages (graphviz, tulip, networkx (python)), but i realized that all of them are specialized at graph-layouting (when there are no coordinates). Correct me when i'm wrong.
I don't know if it is possible to tell these packages that i already have the coordinates, helping the layouting-algorithms.
Next thing i tried is the CGAL library with geomview output -> no luck until now -> ubuntu crashes geomview.
One more question: Is it a better idea to use some non-layouting 2d-plot-libraries risking a plot, which isn't really good to view at (is there more to do than scaling?) or to use some layout-algorithm-based-libraries (e.g. graphviz, tulip, networkx), feed them with the distances between the vertices and hope the layouting-algorithms are keeping the distances while plotting in a good-to-view-at way?
If non-layouting-plotting is the way to do it: which library do you recommend?
If layout-based-plotting is the way to do it: how can i make use of the distances/coordinates in these libraries? And which library do you recommend?
Thanks for all your input!
Sascha
EDIT: I completed a prototype implementation using the PLplot library (http://plplot.sourceforge.net/). The results are nice and should be enough for the moment. I discovered and chosed this library because a related project (VRPH Software Package / Groer) used this plot and the source code was distributed. So the implementation was done in a short amount of time. The API is in my opinion bit awkward and low-level. Maybe there are some more modern (maybe not a c-based library) libraries out there? MathGL? Dislin? Maybe i will try them too.
The nice thing about drawing multiple tours in a vehicle routing problem is that "not so bad" algorithms tend to discover nice non-overlapping and divergent tours which is really good for the eye ;-)
It is not quite clear what you are trying to archive, but if I understand your question correctly, then you could do it using OpenGL. Having vertex coordinates, it should be fairly easy.
You can use Gnuplot with a input text file that contains your solution.
It is convenient to draw the points (vertex) then lines (agents paths) than link them.
To make the plot script easy, you can have a separate file for each vehicle, if the number
of vehicles is known.
check out:
http://www.cleveralgorithms.com/nature-inspired/advanced/visualizing_algorithms.html

How do I write a Perl script to filter out digital pictures that have been doctored?

Last night before going to bed, I browsed through the Scalar Data section of Learning Perl again and came across the following sentence:
the ability to have any character in a string means you can create, scan, and manipulate raw binary data as strings.
An idea immediately hit me that I could actually let Perl scan the pictures that I have stored on my hard disk to check if they contain the string Adobe. It seems by doing so, I can tell which of them have been photoshopped. So I tried to implement the idea and came up with the following code:
#!perl
use autodie;
use strict;
use warnings;
{
local $/="\n\n";
my $dir = 'f:/TestPix/';
my #pix = glob "$dir/*";
foreach my $file (#pix) {
open my $pic,'<', "$file";
while(<$pic>) {
if (/Adobe/) {
print "$file\n";
}
}
}
}
Excitingly, the code seems to be really working and it does the job of filtering out the pictures that have been photoshopped. But problem is many pictures are edited by other utilities. I think I'm kind of stuck there. Do we have some simple but universal method to tell if a digital picture has been edited or not, something like
if (!= /the origianl format/) {...}
Or do we simply have to add more conditions? like
if (/Adobe/|/ACDSee/|/some other picture editors/)
Any ideas on this? Or am I oversimplifying due to my miserably limited programming knowledge?
Thanks, as always, for any guidance.
Your best bet in Perl is probably ExifTool. This gives you access to whatever non-image information is embedded into the image. However, as other people said, it's possible to strip this information out, of course.
I'm not going to say there is absolutely no way to detect alterations in an image, but the problem is extremely difficult.
The only person I know of who claims to have an answer is Dr. Neal Krawetz, who claims that digitally altered parts of an image will have different compression error rates from the original portions. He claims that re-saving a JPEG at different quality levels will highlight these differences.
I have not found this to be the case, in my investigations, but perhaps you might have better results.
No. There is no functional distinction between a perfectly edited image, and one which was the way it is from the start - it's all just a bag of pixels in the end, after all, and any other metadata you can remove or forge all you want.
The name of the graphics program used to edit the image is not part of the image data itself but of something called meta data - which may be stored in the image file but, as others have noted, is neither required (so some programs may not store it, some may allow you an option of not storing it) nor reliable - if you forged an image, you might have forged the meta data as well.
So the answer to your question is "no, there's no way to universally tell if the pic was edited or not, although some image editing software may write its signature into the image file and it'll be left there by carelessness of the editing person.
If you're inclined to learn more about image processing in Perl, you could take a look at some of the excellent modules CPAN has to offer:
Image::Magick - read, manipulate and write of a large number of image file formats
GD - create colour drawings using a large number of graphics primitives, and emit the drawings in various formats.
GD::Graph - create charts
GD::Graph3d - create 3D Graphs with GD and GD::Graph
However, there are other utilities available for identifying various image formats. It's more of a question for Super User, but for various unix distros you can use file to identify many different types of files, and for MacOSX, Graphic Converter has never let me down. (It was even able to open the bizarre multi-file X-ray of my cat's shattered pelvis that I got on a disc from the vet.)
How would you know what the original format was? I'm pretty sure there's no guaranteed way to tell if an image has been modified.
I can just open the file (with my favourite programming language and filesystem API) and just write whatever I want into that file willy-nilly. As long as I don't screw something up with the file format, you'd never know it happened.
Heck, I could print the image out and then scan it back in; how would you tell it from an original?
As other's have stated, there is no way to know if the image was doctored. I'm guessing what you basically want to know is the difference between a realistic photograph and one that has been enhanced or modified.
There's always the option of running some extremely complex image recognition algorithm that would analyze every pixel in your image and do some very complicated stuff to determine if the image was doctored or not. This solution would probably involve AI which would examine millions of photos that are both doctored and those that are not and learn from them. However, this is more of a theoretical solution and isn't very practical... you would probably only see it in movies. It would be extremely complex to develop and probably take years. And even if you did get something like this to work, it probably still wouldn't be 100% correct all the time. I'm guessing AI technology still isn't at that level and could take a while until it is.
A not-commonly-known feature of exiftool allows you to recognize the originating software through an analysis of the JPEG quantization tables (not relying on image metadata). It recognizes tables written by many applications. Note that some cameras may use the same quantization tables as some applications, so this isn't a 100% solution, but it is worth looking into. Here is an example of exiftool run on two images, the first was edited by photoshop.
> exiftool -jpegdigest a.jpg b.jpg
======== a.jpg
JPEG Digest : Adobe Photoshop, Quality 10
======== b.jpg
JPEG Digest : Canon EOS 30D/40D/50D/300D, Normal
2 image files read
This will work even if the metadata has been removed.
There is existing software out there which uses various techniques (compression artifacting, comparison to signature profiles in a database of cameras, etc.) to analyze the actual image data for evidence of alteration. If you have access to such software and the software available to you provides an API for external access to these analysis functions, then there's a decent chance that a Perl module exists which will interface with that API and, if no such module exists, it could probably be created rather quickly.
In theory, it would also be possible to implement the image analysis code directly in native Perl, but I'm not aware of anyone having done so and I expect that you'd be better off writing something that low-level and processor-intensive in a fully-compiled language (e.g., C/C++) rather than in Perl.
http://www.impulseadventure.com/photo/jpeg-snoop.html
is a tool that does the job almost good
If there has been any cloning , there is a variation in the pixel density..or concentration which sometimes shows up.. upon manual inspection
a Photoshop cloned area will have even pixel density(my meaning is variation of Pixels wrt a scanned image)