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my project is to count White fly in an image using matlab, I'm new to image processing so I don't know where to start from , I searched for papers about the topic but I could't find anything useful , my question is to help me start from a point and if you can suggest some papers can help me , thanks .
There is a lot of research in this area, but not specific to Matlab. Try using google scholar to search for papers with "computer vision counting" or similar keywords.
Richard Szeliski also has a very good, free to download textbook on Computer Vision which could be helpful: http://szeliski.org/Book/. Topics like Feature Detection, Segmentation and Recognition might be useful, depending on your exact problem.
When you have an idea of what you want to do, have a look at Matlab's Computer Vision toolbox: http://au.mathworks.com/help/vision/index.html
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Ive been researched Information Visualization techniques application to image collections. I need some image datasets with features. Ideally, would be good find a dataset in a file representing each image attributes value,like this https://archive.ics.uci.edu/ml/datasets/Corel+Image+Features so I could project on my software, but it has been too hard to find, so I am trying to work with matlab algorithms to extract the features. So, I want some datasets.
Here you can find the ImageCLEF 2013 dataset with different features: GIST, Color Histograms, SIFT, C-SIFT, RGB-SIFT and OPPONENT-SIFT.
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I have tried manual detection using LS polynomial fitting here. But that cannot be used in my project as mine has to be a fully automated system.
Take a look at the Scale-Invariant Feature Transform, or SIFT. This video explains it well. You "train" a detector with one or more images of eyelids, and the detector locates similar regions in the input images. It's the de facto general purpose feature detector - although more specialized tools like face detectors are faster.
The "Scale-Invariant" part means that it can detect the same object at different sizes and rotations.
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I am searching for segmenting gray matter from a T1 weighted brain MRI scan. But I could not get the correct tutorial to follow it. Please suggest me an algorithm that works better and accurately to segment the gray matter alone from the T1 wieghted MRI scan image. There are several tools to segment gray matter in matlab but I need algorithm to segment the gray matter. Please suggest me the algorithm.
Why reinvent the wheel? SPM does a good job of segmentation and the MATLAB source code is freely available: http://www.fil.ion.ucl.ac.uk/spm/
You can examine the algorithm that is used and customize it for your own purposes if you wish. It produces probabilistic maps of gray matter, white matter, and csf that you can use in subsequent analyses. There are also a variety of options to complete the segmentation in both normalized and native space. I highly recommend it as a place to get started, and then you can branch off from there depending on your needs.
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I wonder what is the best algorithm for motion detection of human subjects. Keeping in mind that the motion is detected for moving objects with tolerance of leaving out minor changes to the environment. Matlab/OpenCV sources would be great!
Thanks
A long time back i saw this page, where you can see the code of the thesis and the thesis of "A real-world system for human motion detection and tracking" maybe this can help you.
Thesis David Moore
This could to be a good point to begin.
Check out:
www.ensta-paristech.fr/~manzaner/Publis/icvgip04.pdf
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I'm learning about multilayer perceptrons, and looking to tackle some real-world problems in Matlab. Perhaps something like medical diagnosis, or speech recognition... But I'm not really sure where to start here. How should I tackle this?
Geoff Hinton is the man when it comes to multilayer perceptrons. His Science paper from 2006 used a special class of MLP called an "autoencoder" that was successful in digit recognition, facial recognition, and document classification (all of which have real world applications):
Reducing the Dimensionality of Data with Neural Networks
Fortunately, they also published the
Matlab code.