Platform: amd_64
Operating System: Ubuntu 8.10
Problem:
The current release of OpenCV (2.1 at time of writing) and libdc1394 doesn't properly interface with the new USB-interface PointGrey High-Res FireFlyMV Color camera.
Does anyone have this camera working with OpenCV on Ubuntu?
Currently, I'm working on writing my own frame-grabber using PointGrey's FlyCapture2 SDK, which works well with the camera. I'd like to interface this with OpenCV, by converting each image I grab into an IplImage object. When I write OpenCV programs, I use CMake. The example code for the FlyCapture2 SDK uses fairly simple makefiles. Does anyone know how I can take the information from the simple FlyCapture2 makefile so I can include the appropriate lines in CMakeLists.txt for my CMake build routine?
Not a simple answer (sorry) - but.
Generally you don't want to use cvCaptureCam() for high performance cameras beyond initial tests that they work. Even for standard interfaces like firewire It is very limited in what features of the camera it can control, it doesn't handle threading well and the performance is poor - especially at high data rates.
The more common way is to control the camera with the makers own SDK and output frames in a form (cv::mat/iplimage) that openCV can process. All openCV image types are very flexible in being able to share data with the camera API and specify padding/row striping etc so you should be able to design it so there is no unnecessary copying.
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I have never ever asked this kind of question on StackOverflow before, and I wonder if you could help me guys because it is a "bit" vague.
I have to design a project that uses Teensy (simple ARM platform) for getting data from IR camera (Flir, resolution 80x60) over SPI, and streaming these data to Linux/Windows running machine (through USB-serial) and doing something simple with OpenCV.
THE PROBLEM: The project lacks some "inovation". It should not be something very complicated, but rather different approach, or trying something new.
Do you have recommendations/tutorials/books/experience with working with above mentioned things? OR do you see a potential for teying something new?
You might want to check out the OpenCV Cookbook for some ideas.
There is a project using this FLIR with a Teensy. It provides a thermal image using a small LCD screen (without any aditional computer).
https://hackaday.io/project/8994-diy-thermocam
So, the teensy can get data through spi.
Can the teensy send data through usb then ? Probably but you will have to check if the rate is high enough
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Using OpenCV directly on teensy is not possible because of size of library. But you can probably make some basic image processing if the code is small enough.
The FLIR Lepton can be directly interfaced with Linux or Windows computer, so I don't really see the use of Teensy.
I would recommend a Raspberry Pi to interface the FLIR Lepton and then do some image processing. It's well documented on the web.
i want to do a project which uses eye tracking, is it possible to port an open cv code on a microcontroller.
i am new to opencv as well as microcontroller so can any one tell me if it is possible to make a code which works like this vedio.
http://www.youtube.com/watch?feature=endscreen&v=eBtpKAja-m0&NR=1
Q: Can i use an eye detecting opencv code on microcontroller?
A: Yes, you can
Q: Is it possible to port an open cv code on a microcontroller
A: OpenCV is already in the Unix and Android platform. The easiest approach therefore will be to get hold of some embedded device with ARM. There are a lot of help available for the 'OpenCV-ARM' combination.
Beagleboard and RasberryPi are the cheapest embedded ARM devices available for less than $150. Sometimes they come preloaded with Unix boot system and opencv2.0. Thus it would be so easy to run the executable that you created in the computer system.
Be aware of the speed of the processor. If your algorithm is computationally intensive then you wont be quiet satisfied with the output being obtained in the low-end embedded devices.
If some ARM embedded Linux board can fit into your definition of microcontroller, then there is nothing to port.
http://www.google.com/search?q=opencv+arm
I'm currently developing some computer-vision application for blind people. Now we decided to move our studies on mobile apps.
Since OpenCV 2.4, building them for iOS is quite simple due to the two scripts.
The most problem I'm facing is time of processing. I read that most of image processing on iPhone is done with OpenGL. So I was wondering if could be a possibility to build OpenCV with OpenGL support when builded for iOS.
The processing time for very simple operation in OpenCV (on iPhone) is too long for real-time apps, especially if dedicated to blind people who need a rapid feed-back of reality.
Could someone help me?
It is not possible to build OpenCV with OpenGL support for iOS (and OS X). It is unconditionally disabled by the OpenCV's build scripts.
Actually OpenGl is not used in OpenCV for acceleration. So you will not get any speedup even after editing the sources.
I'm new to embedded software, I want to build a Image processing application for my AT91SAM9261-EK development board by Atmel. To make it simple i want to use the OpenCV functions, but i'm not sure how am I going to generate a .bim file for flashing on the brd.
Also can anyone you help me understand the flow / software structure for these kind of applications?
Like, will I need Linux or any other OS, if so where does the actual image processing code which i intend to write using opencv sit ?
Till now for simple codes like Basic LCD project, for this board i'm compiling the code using IAR workbench, so if I want to use the same for opencv functions, is there a way ?
Is there any other open source image processing libraries similar to opencv & easy to integrate with IAR or any other ARM compiler ?
Also it would be really useful if there are any links to some learning documents regarding this
Thanks in advance ?
Depending on your application, I think that CPU is not going to be powerful enough to do any kind of image processing; plus the weirdness of working with a foreign system is not going to make your life any easier.
If using this exact CPU is not super important I'd recommend a Beagleboard or Pandaboard, mainly because Ubuntu has installers targeted to the boards and Ubuntu/Debian offers OpenCV packages out of the box, and this is going to remove a whole lot of hurdles if you're new to embedded development -- basically it turns your dev board into a full-featured computer, just plug in a monitor, keyboard and mouse.
The Raspberry Pi looks to be promising in this regard as well, and you certainly can't argue with the price! (You may be able to install Debian on your board and get access to OpenCV packages this way, but I can't vouch for the ease-of-use of this method compared to Ubuntu, which is difficult enough, especially if you're new to Linux).
We're looking for a package to help identify and automatically rotate faxed TIFF images based on a watermark or logo.
We use libtiff for rotation currently, but don't know of any other libraries or packages I can use for detecting this logo and determining how to rotate the images.
I have done some basic work with OpenCV but I'm not sure that it is the right tool for this job. I would prefer to use C/C++ but Java, Perl or PHP would be acceptable too.
You are in the right place using OpenCV, it is an excellent utility. For example, this guy used it for template matching, which is fairly similar to what you need to do. Also, the link Roddy specified looks similar to what you want to do.
I feel that OpenCV is the best library out there for this kind of development.
#Brian, OpenCV and the IntelIPP are closely linked and very similar (both Intel libs). As far as I know, if OpenCV finds the intel IPP on your computer it will automatically use it under the hood for improved speed.
The Intel Performance Primitives (IPP) library has a lot of very efficient algorithms that help with this kind of a task. The library is callable from C/C++ and we have found it to be very fast. I should also note that it's not limited to just Intel hardware.
That's quite a complex and specialized algorithm that you need.
Have a look at http://en.wikipedia.org/wiki/Template_matching. There's also a demo program (but no source) at http://www.lps.usp.br/~hae/software/cirateg/index.html
Obviously these require you to know the logo you are looking for in advance...