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I have to develop a small application that gets some images and then counts the items in the image. It is something like a satellite image with a road and I need to count the cars.
Can you give me some hints where to start? I am completely lost.
Thanks a lot,
Radu
Have you checked out OpenCV? Emgu CV provides the .NET bindings
Image processing library:
OpenCV or if you have Matlab with the image processing toolbox it would be very nice.
Algorithm wise
Counting cars on a road is not as simple as it appears. Lets suppose they have a invariant scale (say 1.0).
Create yourself a Hough transform algo to vote for rectangles with about the same width and height as your cars.
In your vote buffer find the 'n' greatest vote scores and this is your number of cars.
This is not so complicated and OpenCV can be pretty useful. You can estimate the maximum value of your hough score for each car so you can set thresholds to skip outliers.
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I'm working on a project that is related to duplicate document detection. I've have spent hours and hours googling and learning a lot about OpenCV (it's been a really tough, but an interesting experience altogether, I'm definitely going to start a blog this after everything!). I plan on using BRISK\AKAZE detectors together with FREAK descriptors and LSH matching to compare each document (because the documents are mainly black and white), but I need to calculate exactly how similar the two images are based on percentage, to enable my software make simple decisions afterwards.
I'm open to any ideas or suggestions on my project, and I would love if anyone would be so nice to share some code together with their answers to save me the time of googling my way there :-). Thanks.
EDIT:
Here are samples to explain my problem.
Image 1 is the document I need to get the match for. It is very similar to the all the other documents, but it is different from Image 3, after matching it should have similarity percentage of maybe 90% to Image 3. Image 2 is a duplicate of Image 1, it has been re-scanned and was slightly rotated in the process, it can have a 95% - 98% similarity since it's features are very similar to image 1. Thanks Everyone :).
You should look into SSIM. (Structural Similarity Index). It returns a 0-1 score based on similarities in image structure and pixel values. I don't believe that OpenCV has a pre-made solution for it but there are loads of tutorials for writing your own in OpenCV.
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When i drew line charts using c# with a lot of data(maybe 10 million~100 million), it's not loaded. c# window form was broken.
i can't reduce these data because all of data are important.
Surely it is impossible to show all 10 million data points on a screen. My current screen resolution at 1920x1080 only has about 2M pixels. So even if you show all the points from your data, there will not be enough screen space to show it all.
So you'll need to either reduce your data size by smoothing out the graph data or show only parts of your data at a time.
Use for example Oxyplot - you just bind data, and the library does all the work - zooming, paning, smoothing graphs.
Take a look at a package like HoloView for Python - it supports big pictures with zoom in capabillity.
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My adviser told me to use Accord Framework for C# to extract features and patterns from images. Our project is about image analysis and comparison of tobacco leaves. Does anyone here have an idea on how to do it? Thank you.
This is pretty high level stuff, but from what I've learned in my time faffing with it, I'd use the Accord.Imaging library to scan your pictures. Followed by using the Accord.Neuro namespace to "learn" from some manual data you feed into it.
Seems your goal is to create a program that scans images quickly, gleaning only the useful data from the full image, and then checking for some particular features of the image. I've never used the library, but it looks like it'd be possible to use it.
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I do have a set of image files. Some of the files contains a bar code and I want to separate those from others. In c# how to find the presence of a bar code in an image file??
You have to apply some computer vision algorithms. You can develop them using OpenCV (via P/Invoke in C#), or EmguCV (http://www.emgu.com/wiki/index.php/Main_Page) which is .NET wrapper for OpenCV. There are also libraries made specific for barcode detection - ZXing comes to my mind.
If the bar codes are located at fixed positions, you can simply save these areas from the images to separate images and process them. If you need to locate the barcodes in the first place, you can use EmguCV for pattern recognition.
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I am implementing 2d-bin-packing algorithm in canvas. My task is to place rectangles as optimal as it can be on a canvas.
the following shows how to do it:
http://incise.org/2d-bin-packing-with-javascript-and-canvas.html
BUT, it starts with the origin. I would like to tell the algorithm where to put a rectangle and that the next one not to be on top of him.
What should be changed in the code?
Is there another algorithm to use for it?
I know a better algorithm(in terms of compactness, not speed) than the one you linked to is called MaxRects.
This was my implementation of it in C++. While not fast, it was very effective at packing compactly.
This is a pdf discussing and comparing all sorts of algorithms in terms of both time and compactness.
EDIT:
I threw together an example of an image packed using MaxRects .