A primitive OpenCV data type is one of unsigned charboolsigned charunsigned shortsigned shortintfloatdoubleor a tuple of values of one of these types, where all the values in the tuple have the same type.
A universal OpenCV structure that is able to store a single instance of such a primitive data type is Vec. It is not DataType itself that is used but its specialized versions, such as:. The main purpose of this class is to convert compilation-time type information to an OpenCV-compatible data type identifier, for example:.
So, such traits are used to tell OpenCV which data type you are working with, even if such a type is not native to OpenCV. This mechanism is also useful and used in OpenCV this way for generic algorithms implementations. Template class for 2D points specified by its coordinates and. There is also a cast operator to convert point coordinates to the specified type. The conversion from floating-point coordinates to integer coordinates is done by rounding.
Commonly, the conversion uses this operation for each of the coordinates. Besides the class members listed in the declaration above, the following operations on points are implemented:. Template class for 3D points specified by its coordinatesand. An instance of the class is interchangeable with the C structure CvPoint2D32f. The vector arithmetic and comparison operations are also supported. Template class for specifying the size of an image or rectangle.
The class includes two members called width and height. OpenCV typically assumes that the top and left boundary of the rectangle are inclusive, while the right and bottom boundaries are not. This is an example how the partial ordering on rectangles can be established rect1 rect2 :.
The class represents rotated i. Each rectangle is specified by the center point mass centerlength of each side represented by cv::Size2f structure and the rotation angle in degrees. The class defining termination criteria for iterative algorithms. You can initialize it by default constructor and then override any parameters, or the structure may be fully initialized using the advanced variant of the constructor. Converts to the deprecated CvTermCriteria format. If you need a more flexible type, use Mat.
The elements of the matrix M are accessible using the M i,j notation.We have multiple ways to acquire digital images from the real world: digital cameras, scanners, computed tomography, and magnetic resonance imaging to name a few. In every case what we humans see are images. However, when transforming this to our digital devices what we record are numerical values for each of the points of the image. For example in the above image you can see that the mirror of the car is nothing more than a matrix containing all the intensity values of the pixel points.
How we get and store the pixels values may vary according to our needs, but in the end all images inside a computer world may be reduced to numerical matrices and other information describing the matrix itself. OpenCV is a computer vision library whose main focus is to process and manipulate this information. Therefore, the first thing you need to be familiar with is how OpenCV stores and handles images. OpenCV has been around since In those days the library was built around a C interface and to store the image in the memory they used a C structure called IplImage.
This is the one you'll see in most of the older tutorials and educational materials. The problem with this is that it brings to the table all the minuses of the C language.
The biggest issue is the manual memory management. It builds on the assumption that the user is responsible for taking care of memory allocation and deallocation.
While this is not a problem with smaller programs, once your code base grows it will be more of a struggle to handle all this rather than focusing on solving your development goal. Therefore, OpenCV 2. Therefore, unless you are targeting embedded platforms, there's no point to using the old methods unless you're a masochist programmer and you're asking for trouble.
The first thing you need to know about Mat is that you no longer need to manually allocate its memory and release it as soon as you do not need it. While doing this is still a possibility, most of the OpenCV functions will allocate its output data automatically. As a nice bonus if you pass on an already existing Mat object, which has already allocated the required space for the matrix, this will be reused. In other words we use at all times only as much memory as we need to perform the task.
Mat is basically a class with two data parts: the matrix header containing information such as the size of the matrix, the method used for storing, at which address is the matrix stored, and so on and a pointer to the matrix containing the pixel values taking any dimensionality depending on the method chosen for storing.
The matrix header size is constant, however the size of the matrix itself may vary from image to image and usually is larger by orders of magnitude.
OpenCV is an image processing library. It contains a large collection of image processing functions. To solve a computational challenge, most of the time you will end up using multiple functions of the library. Because of this, passing images to functions is a common practice. We should not forget that we are talking about image processing algorithms, which tend to be quite computational heavy.
The last thing we want to do is further decrease the speed of your program by making unnecessary copies of potentially large images. To tackle this issue OpenCV uses a reference counting system.
Python OpenCV: Converting an image to gray scale
The idea is that each Mat object has its own header, however a matrix may be shared between two Mat objects by having their matrix pointers point to the same address. Moreover, the copy operators will only copy the headers and the pointer to the large matrix, not the data itself. All the above objects, in the end, point to the same single data matrix and making a modification using any of them will affect all the other ones as well.
In practice the different objects just provide different access methods to the same underlying data. Nevertheless, their header parts are different.
The real interesting part is that you can create headers which refer to only a subsection of the full data.Make your thoughts Open source. Share it. Thanx Suraj. You just need to make a small change for that. Use the same cvGet2D to retrieve value. Just you would just need to retrieve the first value.
For those looking for cvMat to IplImage conversion the below link should help. Hey adithya; i want to identify a black spot in a white tablet. Thanks for sharing it buddy I am not clear with the white table but seems your problem could be solved using template matching. Would the "cataract. In the project file? Would it be better to have a function parameter which points to the location? Would that be possible with cvLoadImage? Post a Comment. Getting a digital image into numbers can be very handy for your image processing.
In this post i will brief just that. I am a beginner in OpenCV and i found it very difficult to find material to do this. I was looking for storing a 8-bit image, 3 channel image into a 3D matrix. That's the method i am going to explain in this post. Before i get on with the implementation, i would like to brief about the matrix structure that we are going to use. Its a 3D matrix; the row and column values represent the respective X and Y co-ordinates of the image.
That is each value in the matrix represent a pixel. I am considering a 3 channeled image, so each pixel will have 3 channel values i. For more info on the matrix basic you can refer this link. Following is the method I used. First load a 8-Bit image with 3 channels RGB and create define a matrix structure accordingly. Next use the cvConvert function. That does the work! Now your IplImage is stored into the matrix.
You can retrieve the matrix values just by specifying the corresponding X,Y co-ordinate values in the cvGet2D function. I have used a for loop to print the RGB values of a small portion of the image. Please leave a comment so that know if this post is helpful or not.It is highly optimized for numeric operations and support vectorization and use aligned memory allocators.
When it comes to matrix operations, Eigen is much faster than OpenCV. However, it can be situations when it is necessary to pass Eigen data to OpenCV functions. No copy, minimal overhead and maximum syntax sugar:. Proposed approach does not limited to continuous memory layout - it support expression and blocks as well.
How to convert OpenCV cv::mat to System Bitmap to System ImageSource
If given expression has to be evaluated - it will be evaluated into temporary dense storage and then mapped to OpenCV structure:. This approach gives compiler a lot of hints on actual data layout which helps to generate more efficient code. The drawback of this - if you want to deep dive in Eigen internals be prepared to hardcore. I will use templates as well. We will have template class Eigen2CV and several specializations of this class - for planar types, for blocks, for expression and so on… In addition we will specialize this class with mutable specification which will let us to define at compile time whether mapped object is allowed for writing or not.
By default all derived types will have read-only access. These two classes derives from Eigen::PlainObjectBase class which provides methods to access internal storage buffer. Now we can write two overloads of eigen2cv function for Eigen::Matrix and Eigen::Array. Here is how it looks like for planar data:. Compiler will choose right function depending on the context of src. In case of access right conflicts you will get compile-time error. Image is single channel - there is no way to map multi-channel images to Eigen now.
The dark mode beta is finally here. Change your preferences any time. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. You can treat a matrix or an image as a matrix or an image by calling cvGetMat or cvGetImage.
No data will be copied. If you want to copy the data, use cvCopy. Learn more. Ask Question. Asked 10 years, 4 months ago. Active 8 years ago. Viewed 8k times. Please tell me how to convert image into matrix of pixels and vice versa AndrewS 3, 1 1 gold badge 17 17 silver badges 25 25 bronze badges.
Active Oldest Votes. OwnWaterloo OwnWaterloo 1, 14 14 silver badges 10 10 bronze badges. Dear Mr. OwnWaterloo, I have an image and I would like to convert it to a matrix.
What is the difference? After converting the original image to this matrix by cvCopychange made in one has no effect on the other. On the other hand, cvGetMat won't allocate anything, just use its arguments and be careful with their lifetime. The matrix returned by cvGetMat will share the data with the original image. BTW: the notification sent by SO escaped my notice, sorry for late I understand the difference.Computer Vision with Python and OpenCV - Images, Numbers, and NumPy
Sign up or log in Sign up using Google. Sign up using Facebook. Sign up using Email and Password. Post as a guest Name. Email Required, but never shown. The Overflow Blog.OpenCV is an open source computer vision library which can be used for a wide variety of things such as face recognition, people detection, motion tracking, video editing and image manipulation. For my undergraduate project, I made use of the OpenCV libraries to create a facial recognition system.
It used a webcam to detect ID cards in my project, I made use of ACU ID cards and find the photograph on it, then used facial recognition to match the presented ID card with one in its database. More recently, I utilised the OpenCV libraries in a piece of research to build software to perform automatic data capture from hospital videos to save the human-effort required in data capture.
In my undergraduate project, the core output was the dissertation report and not the software, thus the software was created to perform its functionality but without a clean or user-friendly interface.
As such, displaying information from the OpenCV libraries was done using the cv::imshow method, rather than embedding the cv::mat into a GUI of my design.
For my more recent software development, I opted to do this to produce a clean GUI that I could use to demonstrate my research to those outside my field. The GUI needed to display the frames of the video as it was playing so the user could see the video at the same time as it was being analysed. However, this meant converting the cv::mat image to an image source to display in the image control. This was done by converting the cv::mat to a System Bitmap first as a go-between the cv::mat and image source data types and then converting the bitmap to an image source.
To display a video in a GUI, simply use a timer to continue calling frames from the engine as they change and display them in the GUI.
Computer Scientist currently undertaking an Engineering Doctorate degree discussing computing, programming, research and racing. I have exactly the same code as you but for some reason my application gives me the following error: AccessViolationException was unhandled. Attempted to read or write protected memory. This is often an indication that other memory is corrupt.
Hi Drekbende, It sounds like the bitmap memory is corrupted somehow during run. What code do you have? I can't promise to fix it - it's been a while since I looked at OpenCV stuff so I'll be a little rusty but happy to take a look and see if there's any obvious issue with the conversion. Best regards, Fraser. Well now, I have a chunk of code but I don't think it's readable in this comment section but let's have a try. OpenCvWrapper. ApplyFilter ; pictureBox1. I try to reply to everyone that comments, I'm just a bit lax at checking my emails to see that a comment has come in so apologies for the delayed response!
The only thing I can think of from looking at that code would be either the Bitmap does not like the PixelFormat you've chosen, or the pictureBox1. Image is in a different thread to the bitmap.Is there any way ,in which I can convert a Mat object into an double array? I have some image proccesing algoritms that I don't know how to use them on Mat objects, but I can use them if I can find a way of transformingon double's!
I'm a novice in Opencv! If the Mat's are converted into double'sand the Mat's are on 3 channels, do I lose some information, do I have to convert the Mat image in gray?
What approach can I use? You can access to pixel data using method at or Ptr. I think you should think in the other way transform your algorithm to be compatible with opencv Mat.
If you have a submatrix of a Mat src Rect x, y, w, h normaly a row is continous, so you can set a pointer to the begining of a row. Edit: You use a 3 channel image, above example is for 1 channel image.
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So storage order is explained here. The data access is similar to example above with respect to the 3 channel storage. Although this is almost a 4-year old question,it is worth to note that for a 2D matrix access,there is something strange: the ptrDst is declared for a 1D array ,and then it is later used as a referenced 2D array: ptrDst[i][j]. Asked: Area of a single pixel object in OpenCV.
OpenCV for Android 2. Can't compile.
Using OpenCV's stitching module, strange error when compositing images. First time here? Check out the FAQ! Hi there! Please sign in help. About double and 3 channels : a real number is not vector. It's dfficult to answer to your question without knowing your problem.
JPG" ; img. Edit2: code corrected. Thanks to LBerger.