I have two images.
One is big and the other is small. I need an image comparison code/library which will search for the small one in the big one and give me the location and the percentage of the compared.
Suggestions?
Emgu is opencv (open computer vision) in .Net.
http://www.emgu.com/wiki/index.php/Main_Page
This will have more than enough functionality to do what you are asking for.
EDIT: I am assuming that C# is a key requirement.
Related
is there a way to grab a screen capture of a specific section of the screen and compare it to another image already store in disk. And if the image is identical, it would prompt something.
If you are trying to compare an image (or part of it) with another images, I searched internet and found that leadtools has correlation functions that compare an image with all the areas of the same dimensions in another image. For more information, see this link: http://www.leadtools.com/help/leadtools/v175/dh/po/leadtools.imageprocessing.core~leadtools.imageprocessing.core.correlationcommand.html
OR
This project may be what you're looking for:
https://github.com/cameronmcefee/Image-Diff-View-Modes/commit/8e95f70c9c47168305970e91021072673d7cdad8
Check http://www.developerfusion.com/code/4630/capture-a-screen-shot/ for examples on how to capture the screenshot.
The image comparison is a lot more complicated. The image that is stored on disk might have a different size, a different aspect ratio, or a different depth. Unless you can be sure that the screenshot and the image on the disk are absolutely identical, you'll have to look at a method that identifies similar images.
Take a look at the pHash Demo, which takes two images and outputs a similarity score. The algorithm it uses is pretty straightforward, and is available on the website.
I have to recognize digits within an image from video stream and there are several more things, that should make recognition easier:
1) it is fixed font 6x8, all symbols are equal width
2) I know exact positions of digits, they are always rectangular, are not rotated/sqewed/scaled, but there may be some distortions because of air transmission glitch.
3) It is only digits and .
4) digit background is semi black (50% opaque)
I've tried tesseract v2 and v3, but .NET wrappers aren't perfect and recognition error was very large, even if I trained with custom font, as far as I understand that is because of small resolution.
I've made very simple algorithm by my self by turning image to black and white and counting matching pixels between original font image and image from stream, it performs better than tesseract, but I hink more sophisticated algorithm would do better.
I've tried to train AForge using ActivationNetwork with BackPropagationLearning and it fails to converge(this article first part, as long as I don't need scaling and several fonts http://www.codeproject.com/Articles/11285/Neural-Network-OCR, as I understand code in article is for older version of AForge), bad thing is, that this project is not supported anymore, forum is closed and google groups as I understand too.
I know there's OpenCV port to .NET, as far as I see, it has different network approaches than AForge, so questiton is which approach would fit best.
So is there any .NET framework to help me at this, and if it supports more than one neural network implementations, which implementation would fit best?
For fixed size fonts at a fixed magnification, you can probably get away with a less-sophisticated OCR approach based on template matching. See here for an example of how to do template matching using OpenCV (not .NET, but hopefully enough to get you started.) The basic idea is that you create a template for each digit, then try matching all templates at your target location, choosing the one with the highest match score. Because you know where the digits are located, you can search over a very small area for each digit. For more information on the theory behind template-matching, see this wiki article on Cross-correlation.
This is actually the basis for simplified OCR applications (usually for recognizing special OCR fonts, like the SEMI standard fonts used for printing serial numbers on silicon wafers.) The production-grade algorithms can also support tolerance for scaling, rotation and translation, but the underlying techniques are pretty much the same.
Try looking at this project and this project too. Both projects explain how OCR works and shows you how to implement it in C# and .NET.
If you are not in an absolute hurry I would advise you to first look for a method that solves the problem. I've made good experiences with WEKA. Using WEKA you can test a bunch of algorithms pretty fast.
As soon as you found the algorithm that solves your problem, you can either port it to .NET, build a wrapper, look for an implementation or (if it's an easy algo) rebuild it in .NET.
Hi and thanks for looking!
Update
For the sake of clarity, a third-party .NET library is just fine. Preferably an open-source or free one. The solution need not be native .NET.
Background
I am working on an enterprise web application for which the client has given us thousands of pages of content in MS Word documents that we have to parse, extract data, and send to the content database.
Within these docs are various embedded images representing a larger original image in a separate folder.
The client did not provide any paths to the original source image, so when we see content with an embedded image in the MS Word doc, we have to go through several "assets" folders and look for the corresponding image which is extraordinarily time consuming.
We are already using DocX to parse the documents, so you can assume that we have a list of bitmap images to loop through that we have pulled from the document.
Question
Given a list of bitmaps that we just extracted from the document, how do we search a different folder containing hundreds of images, for the matching image, and then return the file path to it?
TinEye.com does this over the web. I am wondering if, using System.Drawing or something, we can do it on a PC with C#.
Thanks!
Matt
Hate to propose an answer to my own question, but I think I might be on to something here. Here is heuristic/pseudo code for a C# forms app--your thoughts are appreciated:
Part 1
Using System.IO, traverse the "assets" folders and get all images.
For each image, Base64 encode it.
Take the resulting string and place in an XML file:
<Image>
<Path>C:\SomePath</Path>
<EncodedString>[Some Base64 String]<Encoded String>
</Image>
Now we have an XML file containing all original images, in Base64 form, along with their file path.
Part 2
Using DocX, extract all images from MS Word Doc.
For each image, use Linq-to-Xml to search for an exact match in the XML file from Part 1.
If there are no exact matches, start iterating the XML file and computing the Levenshtein distance.
While in the foreach store the XML node Id (or file path) and Levenshtein Distance as a key value pair in an object.
Take the k/v pair with the lowest LD score and return the file path.
For performance, set tolerance so that the foreach stops if a certain original image has an acceptably low LD score when compared to the image extracted from the document.
Since this is a one-off task, I don't need instant performance. So, I could run this tonight before leaving the office and, hopefully, come back tomorrow to a list of paths connecting the original images to the ones embedded in the docs.
UPDATE
The heuristic above worked beautifully! I ended up using the Sift library to efficiently calculate distances between Base64 strings. Specifically, I used their FastDistance() method. Having 100% accuracy on finding the images I need, even if the angle from which the photo was taken is slightly different.
There is no built-in algorithm in the .NET framework for generating image similarity. You'd need to use a third-party library or do it yourself. Lots of image similarity algo questions on SO:
Algorithm for finding similar images
How can I measure the similarity between two images?
comparing images programmatically - lib or class
One more, for .NET: Are there any OK image recognition libraries for .NET?. This one refers you to AForge, which seems to have the algorithm that you are after.
According to this SO answer to a similar question, you should look at OpenCV and VLFeat. The former has a C++ API and the latter a C API, so you would need to write your own P/Invoke wrapper or perhaps wrap them in a C++/CLI facade, which you could call from C#.
I am looking for a way to auto-straighten my images, and I was wondering if anyone has come across any algorithms to do this. I realize that the ability to do this depends on the content of the image, but any known algorithms would be a start.
I am looking to eventually implement this in C# or PHP, however, I am mainly after the algorithm right now.
Is this possible with OpenCV? ImageMagick? Others?
Many thanks,
Brett
Here is my idea:
edge detection (Sobel, Prewitt, Canny, ...)
hough transformation (horizontal lines +/- 10 degrees)
straighten the image according to the longest/strongest line
This is obviously not going to work in any type of image. This is just meant to fuel the discussion.
Most OCR programs straighten the scanned image prior to running recognition. You probably find good code in the many open source'd OCR programs, such Tesseract
Of course this does depend on what type of images you want to straighten, but there seems to be some resources available for automatic straightening of text scans.
One post I found mentioned 3 programs that could do auto-straightening:
TechSoft's PixEdit 7.0.11
Mystik Media's AutoImager 3.03
Spicer's Imagenation 7.50
If manual straightening is acceptable, there are many tutorials out there for how to straighten them manually using Photoshop; just google "image straightening"
ImageMagick has the -deskew option. This will simply rotate the image to be straight.
Most commercial OCR engines like ABBYY FineReader and Nuance OmniPage do this automatically.
The Leptonica research library has a command line tool called skewtest which will rotate the image.
I have not found a library which can take an image which has been distorted in any other way (like pin cushion or if it has been moved during a scanning operation, or removing the warp at the edge of a book). I am looking for a library or tool that can do this, but cannot find one.
Patrick.
Can I compare 2 images and show the difference using C#?
How?
Sure you can. One (slow) way to do so would be to create a new empty image and then use GetPixel and SetPixel to construct the difference image.
Could be useful perform an image substraction (maybe better in GrayScale mode) as shown here:
How to subtract one bitmap from another in C#/.NET?
There is technology called SIFT( Scale Invariant Feature Transform ).This algorithm generates a feature file from an image in which it has salient points of that Image. This file is called SIFT feature.
You have to generate the SIFT feature file for the images that you want to compare. Then this technology has a matching function which you can use to compare the feature files. This function returns a number. the higher the number the more similar the images. in this way you find the most similar images from within a set.