I want to simulate my protocol in Matlab. I do not know about any toolbox nor i get any information about WSN coding in Matlab.
I want to know about it.
regards,
You can use Low Energy Adaptive Clustering Hierarchy (LEACH) cluster based routing protocol in WSN:
http://www.mathworks.com/matlabcentral/fileexchange/25853-wireless-networks
And you can write your own simulator using the MATLAB scripting language. Examples:
SimEvents, Prowler, TrueTime and Complex Networks Package
Hope this helps.
Related
I want to do hand gesture recognition with hmm in matlab. I studied the theoretical materials in both hmm concept and hmm in mathwork . But I need to see some real examples which uses matlab instructions for dealing with hmm. I searched in the web but could not find a good one. Does any one know a reference which uses matlab instructions in a hmm process?
I suggest you look at the toolbox by K. Murphy and its tutorial.
The built-in hmm functions in Matlab are pretty limited I find (though I did not use the very last edition of Matlab). However you can look at the Matlab tutorial too.
Finally, you can check this toolbox. It contains a demo file.
On a side note, be aware that your question is somewhat off-topic here. Adding some code to show that you a least tried something and clearly spot what is causing you trouble (training the model? formatting the data? applying the Viterbi algorithm?) would make this question much more interesting to the community.
I'm looking for good library for camera calibration, I'm aware of Camera Calibration Toolbox for Matlab and OpenCV. The problem with the toolbox is that it is in Matlab and not very friendly for modifications. OpenCV on the other hand seems to be less precise (see Suriansky).
So are there any alternatives?
The paper you cite is rubbish: whoever wrote it did not bother to actually read the code.
The Matlab toolbox uses exactly the same calibration algorithms as the OpenCV code: Zhang's for the initial estimation, followed by a round of bundle adjustment. The reason they are very similar is that the author of the original implementation of the Matlab toolbox worked for a while with the Intel team that produced the calibration code in the very first release of OpenCV.
Any differences among the results they produce are most likely due to different configurations of the control parameters.
I don't understand what you mean by "not very friendly for modification". If you have Matlab, and your application can use it (it's slow), J.Y. Bouguet's code is quite easy to read and modify. On the other hand, I always found the OpenCV codebase somewhat annoyingly low-level (but understandably so, given the stress on performance).
One alternative is the camera calibration functionality in the Computer Vision System Toolbox for MATLAB. Specifically, check out the Camera Calibrator and the Stereo Camera Calibrator apps.
As mentioned by Francesco, both Matlab and OpenCV use the Zhang method. As 2022, OpenCV offers a larger range of distortion parameters thus offering more precision in the pose estimation results. However, all parameters might not be required at once. More details on these parameters are provided in the documentation:
https://docs.opencv.org/4.x/d9/d0c/group__calib3d.html#ga3207604e4b1a1758aa66acb6ed5aa65d
As an alternative solution to both OpenCV and Matlab, I would definitely recommend CalibPro, a web platform that allows you to upload your data and get your calibration parameters in a matter of minutes without a single line of code. CalibPro is fully compatible with OpenCV camera parameters. The platform is rapidly developing and will provide more than the pinhole camera model in the near future.
[Disclaimer]: I am the founder of CalibPro. I am happy to take any feedback on our platform or help people with their calibration.
I am using an Arduino to control a car and I want to make it autonomous by using a webcam to see the object I want and make the car move to this location. I need several things:
MATLAB code
Interface between MATLAB and Arduino
How do I connect between them (software, not hardware)
I need any tutorial to learn or any instructions to make my project. I see many people have done this before, but unfortunately they did not mention how to start these kind of projects.
This question is fairly broad, so I apologize in advance for my somewhat general response.
The easiest way to interface a webcam with MATLAB is to make use of the Image Acquisition Toolbox. This link provides documentation detailing how to do this.
There is a good chance that you'll also want to make use of the Image Processing toolbox in MATLAB to be able to process the acquired images to determine where to go. See this doc. Though, after you've determined more specifically how you plan to process these images, there are probably numerous algorithms that you could find online that would not explicitly require this toolbox.
As far as interfacing with Arduino is concerned, there is a support package from the MathWorks that allows you to interface MATLAB code and Simulink models with Arduino. See this link
The only other general suggestion that I have is to consider using Simulink for this project rather than MATLAB. I feel that the model based approach of Simulink is a much better fit when designing control systems.
I hope that this helps you get things started.
I saw that the tool weka is having a gui interface. This gui interface is very easy for non coding users to classify data sets into classes. Matlab is very difficult since say for example making a neural network you need to write code and to do that you need to have a solid understanding of whats going on. Are there other tools like weka or else is there a plugin to matlab that gives more power to it?
RapidMiner has a functional GUI, and will work for both classification and clustering. It is the most popular open-source (free) data mining application available as of 2012.
RapidMiner: http://rapid-i.com/
It also has numerous training videos and tutorials that you can follow along with - I learned basic clustering methods using a K-means cluster method in about 3 hours. See the Vancouver Data blog for some great RapidMiner analytics videos. Top-notch stuff, really.
Vancouver Data (Neil McGuigan): http://vancouverdata.blogspot.com/
As a bonus, you can install the Weka plug-in, which then gives you GUI Weka. All of the add-ons are free and well-integrated. Other add-ons include a GUI 'R' (the stats program), Reporting Services, Text and Web Analytics, etc. It is fairly simple to use straight 'out of the box' (IMO).
Weka is very (very) powerful and you can write your own classifier if that's what you need to do.
Between Matlab and Weka there's pretty much nothing you can't do in terms of Machine Learning.
You might want to check out Netlab toolkit for Matlab, which is a neural network toolkit developed by a Professor at Aston University - it is available from http://www1.aston.ac.uk/eas/research/groups/ncrg/resources/netlab/
Hey guys, Am wondering if anybody can help me with a starting point for the design of a Neural Network system that can recognize visual patterns, e.g. checked, and strippes. I have knowledge of the theory, but little practical knowledge. And net searches are give me an information overload. Can anybody recommend a good book or tutorial that is more focus on the practical side.
Thank you!
Are you only trying to recognize patterns such as checkerboards and stripes? Do you have to use a neural network system?
Basically, you want to define a bunch of simple features on the board and use them as input to the learning system. It can often be easier to define a lot of binary features and feed them into a single-layer network (what can become essentially linear regression).
Look at how neural networks were used for learning to play backgammon (http://www.research.ibm.com/massive/tdl.html), as this will help give you a sense of the types of features that make learning with a neural network work well.
As suggested above, you probably want to reduce your image a set of features. A corner detector (perhaps the Harris method) could be used to determine features in the checkerboard pattern. Likewise, an edge detector (perhaps Canny) could be used in the stripes case. As mentioned above, the Hough transform is a good line detection method.
MATLAB's image processing toolbox contains these methods, so you might try those for rapid prototyping. OpenCV is an open-source computer vision library that also provides these tools (and many others).