What is the best way to open an image, manually manipulate the pixels as floats, normalize the pixels back to 8bit int values (0-255) and save the new image.
I found deferment codes use different variable types and commands, should i use Iplimage or mat, imread, and so on...
i would really appreciate a code example
Thanks!
You may want to look at the tutorial section provided in the OpenCV docs: OpenCV Tutorials. Especially "Introduction to OpenCV" and "core module. The Core Functionality" are the chapters you should be most interested in.
Refer here. This gives the basic code sample.
Related
I am trying to perform text image restoration and I can find no proper documentation on how to perform OMP or K-SVD in C++ using opencv.
I have over 1000 training images of different sizes so do I divide images into equal sized patches or resize all images? How do I construct the signal matrix X?
What other pre-processing steps are required for sparse coding? How to actually perform K-SVD on color images?
What data type is available in OpenCV for an image dictionary and how do I initialize the Dictionary D?
I have these very basic questions and have tried to use various libraries but they don't make the working very clear.
I found this code useful. This is the only implementation in opencv I have come across so far. I guess it uses a single image for dictionary learning whereas I have to use at least 1000 images. But it certainly provides a good guideline.
As you know there is no opencv official tutorial for video module. That tutorial section is empty. I googled but couldn't find anything good. Any of you know a good OpenCV video module tutorial in c++?
Actually, I need to capture humans, then identify the colour of their T-Shirts
you just want to capture video stream or apply some algo on it or what?
check this
http://www.cc.gatech.edu/~daleshin/OpenCV_Tutorial.pdf
Here is a small example on opencv docs to capture from cam.
http://docs.opencv.org/modules/highgui/doc/reading_and_writing_images_and_video.html
Maybe this help you to detect peoples
http://docs.opencv.org/modules/gpu/doc/object_detection.html
These books from opencv.org may be useful for you
http://opencv.org/books.html
You can do this by using haarcascade xml already provided in opencv.
Then you can check the color of t-shirt by applying simple opencv filters to extract color.
Haarcascade xmls are available of full human body, upper half, lower half etc.
I'm trying to detect an object using opencv and Visual Studio Ultimate using C++. I'm having problems concerning cv::Mat, I cannot find any example of object detection with that kind of variable but just with IplImage. I tried to use an IplImage code and convert it to Mat, but it didn't work. But i don not want to use IplImage, my first part of code is in Mat and I want to keep using it.
What I'm trying to actually do is to detect the BIGGEST rectangle in the image stored from the cam, after thresholding it.
I have already done the threshold part and it's ok, it works and i can se my object (in white) moving in a black background.
Could someone help me with the tracking part? I have seen on the net some blob filtering solutions but they were way too difficult for me! If you can come up with an easy one it would be better.
thank you!
cv::Mat is the new image class in opencv. I think the most algorithms still use IplImage. For this reason I have asked times ago the following:
openCV mixing IplImage with cv::Mat
For recognition of objects I would say watch the cvMatchTemplate function of opencv. There is also the mat version cv::matchTemplate. There are also other object recognition methods but they are a bit more difficult to implement ;)
I dont know if I maybe understood your other question right but I think you wannt to recognze rectangle in your image. Maybe watch this tutorial:
http://docs.opencv.org/trunk/doc/tutorials/imgproc/imgtrans/hough_circle/hough_circle.html
I don t know any standard algorithm for rectangles maybe you will need to code it yourself
cv::Mat encapsulate the lower level IplImage and other formats. Regard detection, there is a sample that you could find useful: squares. I googled for it, and found also this other question, that's more recent and could be of interest to you.
I want to read the contents of every pixel in an image i have and convert it to a bit-stream (raw bits) or contain it in a 2-D array . Which would be the best place to start looking for such a conversion?
Specifics of the image : Standard test image called lena.bmp
size : 256 x 256
Bit depth of pixel : 8
Also I would like to know the importance of the number of bits per pixel with regards to this question since packing and unpacking will also be incorporated .
CImg is a nice simple, lightweight C++ library which can load and save a number of image formats (including BMP).
It's a single header file, so there's no need to compile or link the library. Just include the header, and you're good to go.
You should investigate OpenCV: a cross-platform computer vision library. It provides a C++ API as well as a C API, and it supports many image formats including bmp.
In the C++ interface, cv::Mat is the type that represents a 2D image. A simple application that loads and displays an image can be found here.
To learn how to access the matrix elements (pixels) you can check these threads:
OpenCV get pixel information from Mat image
Pixel access in OpenCV 2.2
Common Matrix Operations in OpenCV
OpenCV’s C++ interface offers a short introduction to cv::Mat. There has been many threads on Stackoverflow regarding OpenCV, there's a lot of valuable content around and you can benefit a lot by using the search box.
This page has a collection of books/tutorials/install guides focused on OpenCV, but this the newest official tutorial.
I want to process an image in C++. How can I access the 3D array representing the JPEG image as is done in MATLAB?
I'd suggest using OpenCV for the task; C++ documentation is available here. The relevant (I believe) data structure which you'd have to use is the Point3_ class, which represents a 3D point in the image.
Well, I've never used MATLAB for such a task, but in C++ you will need some JPEG loader library like OpenIL or FreeImage. These will allow you to access the picture as byte arrays.
FreeImage's FreeImage_GetBits function has a detailed example in the documentation on how to access per pixel per channel data.
BTW, if you plan to do image processing in C/C++, I'd suggest you to check out the Insight Segmentation and Registration Toolkit and OpenCV.