In OpenCV, the type of the elements in a cv::Mat object could be for instance CV_32FC1, CV_32FC3 which represent 32-bit floating point with one channel and 32-bit floating point with three channels, respectively.
The CV_32FC3 type can be used to represent color images which have blue, green and red channels plus an alpha channel used to represent transparency, with each channel getting 8 bits.
I'm wondering how the bits being allocated in CV_32FC1 type, when there's only one channel?
32F means float. The number after the C is the number of channels. So CV_32FC3 means 3 floats per pixel, while CV_32FC1 is one float only. What these floats mean is up to you and not explicitly stored in the Mat.
The float is stored in memory as it would in your regular C program (typically in little endian).
A classical BGR image (default channel ordering in OpenCV) would be a CV_8UC3: 8 bit unsigned integer per channel in three channels.
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Does the second channel of a C2 image represent the alpha channel or do they just fill the gap between C1-C3,C4?
You are mistaking colorspaces with channels. For example you have a greyscale colorspace, which is represented with 1 channel. Then you have BGR with 3 channels, and BGRA with 4. Here the 4th channel is the Alpha value. OpenCV supports several types of colorspaces.
OpenCV is opened to your needs, in some cases you have a mat with 2 values per pixel, for example Dense Optical Flow results, which have a vector of movement of each pixel (x,y vector). You may even create a greyscale image with alpha value for whatever reason or algorithm you have... in this case it will be a CV_8UC2. However this is not a standard colorspace in OpenCV, and a lot of the algorithms have hard constraints on the color space so they may not work with this Mat type.
A cv::Mat can have more than 4 channels even (up to 512 the last time I checked, for more info check the constant CV_CN_MAX), but beware that this may not work with all of OpenCV functions and it will more like a container to your custom algorithms.
i don't understand when opencv documentation mention the term "channel" . Does it mean the channel as in digital image ? or it is something else ?
So as OpenCV is an image processing Library, So A given image can be assumed as 2D matrix with each element as a pixel. Now since there are various types of image formats like Gray, RGB or RGBA, etc. each format is different as to how many colors it(pixel) can support. For example the pixels of Gray image take values in range 0-255 so to represent each gray pixel we need single uchar value, so it has single channel, similarly the pixels of RGB image can take values from 0-16777216 and to represent each RGB pixel, we need 3 uchar values, (256^3 = 16777216), hence it is 3 channels, similarly RGBA has 4 channels, the last channel is used for storing the alpha(transparency) value.
I'm reading a code, in this code I can not understand why we use Mat_<uchar> for image (in opencv) for use:
thereshold
what is the advantage of using this matrix?
OpenCV threshold function accepts as source image a 1 channel (i.e. grayscale) matrix, either 8 bit or 32 bit floating point.
So, in your case, you're passing a single channel 8 bit matrix. Its OpenCV type is CV_8UC1.
A Mat_<uchar> is also typedef-ined as Mat1b, and the values of the pixels are in the range [0, 255], since the underlying type (uchar aka unsigned char) is 8 bit, with possible values from 0 to 2^8 - 1.
I came across the type Vec3b in OpenCV. I just couldn't find a description if this type and why we use it.
Do you know of any reference that describes such type, or, if you can clarify it this would be very much appreciated.
Thanks.
Vec3b is the abbreviation for "vector with 3 byte entries"
Here those byte entries are unsigned char values to represent values between 0 .. 255.
Each byte typically represents the intensity of a single color channel, so on default, Vec3b is a single RGB (or better BGR) pixel. So Vec3bVar[0] might be the blue color part, [1] green and [2] red.
But it could be any other 24 bit 3 channel pixel value like HSV.
vec3b is defined as 3 uchars vec: From OpenCV documentation:
typedef Vec<uchar, 3> Vec3b;
depth Pixel depth in bits. The supported depths are:
IPL_DEPTH_8U Unsigned 8-bit integer
IPL_DEPTH_8S Signed 8-bit integer
IPL_DEPTH_16U Unsigned 16-bit integer
IPL_DEPTH_16S Signed 16-bit integer
IPL_DEPTH_32S Signed 32-bit integer
IPL_DEPTH_32F Single-precision floating point
IPL_DEPTH_64F Double-precision floating point
What these value actually stands for?
How much bits presents each one?
What is the difference between:
Unsigned 8-bit integer and Signed 8-bit integer ?
Unsigned 16-bit integer and Signed 16-bit integer ?
If they demands 8 and 16 bit respectivly?
What's the sense to use data types with floating point?
An unsigned 8 bit has values from 0 to 255, while a signed 8 bit has values from -127 to 127. Most digital cameras use unsigned data. Signed data is mainly the result of an operation on an image, such as a Canny edge detection.
The reason for higher bit depth images, such as 16 bit, is more detail in the image. This allows more operations, such as white balancing or brightening the image, without creating artifacts in the image. For example, a dark image that has been brightened to much has distinct banding in the image. A 16 bit image will allow the image to be brightened more than an 8 bit image, because there is more information to start with.
Some operations work better with floating point data. For example, a FFT(Fast Fourier Transform). If too many operations are done on an image, then the error from rounding the pixel values to an integer every time, start to accumulate. Using a floating point number mitigates this, but doesn't eliminate this.