OpenCV aka open Source Computer Vision Library is a BCD licensed library, is used to analyzing and processing for all the images and videos. It is an open-source library that includes hundreds of computer vision algorithms. It is capable enough to identify faces, objects, and even handwriting by processing images and videos.
Below are few major features of Opencv
Q1. Please explain what is OpenCV?
OpenCV is a software released in June 2000 by the intel corporation. It mainly deals with real-time things such as videos, image, & machine learning. It is used in both the fields i.e., academics, & commercial.
Some most common application of OpenCV is:-
Q2. For what OpenCV is used?
OpenCV is the open-source vision ( To promote and protect open-source software and communities ). OpenCV looks after image processing, face recognition, patterns, videos & machine learning.
There are some library modules of OpenCV:-
Q3. What is OpenCV image processing?
Image Processing is a method to perform some operations on an image, in order to extract some useful information from it.
Sub-tasks can be categorized as follows:-
Q4. For what sobel is used in Opencv?
Sobel Operation is used for detecting the edges of an image in vertical & horizontal direction both.
Sobel() keyword is used to apply Sobel operation in the image. Sobel(src, dst, ddepth, dx, dy)
The following parameters are given below:-
Q5. How many types of image filters are available in OpenCV?
There are various filters available in OpenCV, some of them are listed below -
inear image filtering - In addition to multiplication by the scalar value, each pixel can also be increased or decreased by a constant value.
It is written in the form:- g(i,j) = K x f(i,j)
2D linear image filtering - In 2D linear image mapping the operation is defined first by superimposing the kernel matrix on the original image, then taking the product of the corresponding pixels and returning a summation of all the products.
Box filtering - Box filtering is used for blurring the image.
Non-linear image filtering - Many times linear filter work however in some cases performances can be increased by non-linear image filtering. It is more complex than the linear one.
Median image filtering - It is similar to other filters but it uses the median value as it is non-linear. It is used for removing noise from the image.
Q6. How to connect GPU with opencv?
GPU is used to direct control of transferring data between CPU & GPU.
With these requirements, anyone can connect GPU with the OpenCV -
Q7. What is computer vision.Enlist it few applications?
Computer Vision is a field of AI & computer science within deep learning at the moment. According to Sockman & Shapiro.
Computer Vision is “to make useful decisions about real physical objects and scenes based on sensed images” .
The application of Computer vision are :-
Q8. What are Erosion and Dilation in OpenCv?
Erosion & Dilation both are basic morphological operations that are used for image processing (shapes & all). Now we discuss further about the erosion & dilation:-
It is very similar to soil erosion as the idea is the same, it is used to remove noise from the image & the function of erosion is performed by the by erode() function.
It is opposite of the erosion if we want to remove the noise from image erosion is come after dilation. It works on shape or size, generally square or circle.
Q9. What is use of Mat class in OpenCV?
Mat class is mainly based for storing the image (pixel value). It has two parts:-
The parameters which you add to the cv::Mat are :-
Q10. What is Haarcascade?
Haar cascade is an algorithm used for detecting or identifying the objects in the other images. It is a machine learning approach.
In Haar cascade there are two types of images:-
1. Positive Image
2. Negative Image
The algorithm has four stages:-
1. Haar Feature Selection
2. Creating Integral Images
3. Adaboost Training
4. Cascading Classifiers
OpenCV does this by converting the computer vision of virtual information into vector space. After that, we can identify features and patterns from the vector space and perform mathematical operations on these features. Along with this, you can also convert the images into other color scales to have a better view of features.
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|The speed of executing the programs is more than MATLAB||The programs take more time to execute than OpenCV.|
|OpenCV is based on C.||MATLAB is based on C|
|OpenCV program needs ~ 70MB of RAM to run in real life.||MATLAB needs a vast amount of memory|
|It is free of cost, so you can use it freely.||To use MATLAB under the user license, you have to pay USD 2150|
|The learning curve is stiff, which means it is not easy to learn OpenCV.||MATLAB is a comparatively simple language to understand and learn.|
OpenCV doesn't have its IDE.
|MATLAB comes with its IDE.|