OpenCV work in image recognition is a highly optimized source. Also, it provides the easiest computer vision and image recognition framework.
What Is OpenCV And Its Application?
Open Source Computer Vision Library or OpenCV is one of the top popular libraries. It ill helps us in developing systems. It can also process images and real-time video using image recognition/computer vision.
In the year 1999 OpenCV was created by Gary Brodsky. Also, 2000 is the year it was released.
Optimized C/C++ is the library based on OpenCV. Also, it is supported by Java and Python.
As of now, OpenCV has a large number of a user. Because of its plainness, processing time, and high need in computer vision applications.
Furthermore, the OpenCV library has a lot of optimized algorithms. These algorithms can be used in many applications. Such as,
- Identifies objects
- Identifying and recognizing faces
- Categorizing humans action in videos
- Can track camera actions
- Tracking moving objects
- Extracting 3D models of objects
- Can follow eye movements
- It can find similar images from the image database
- Recognizing the scenery and other landmarks
- Establishing the markers to overlay augmented reality
And many more. And it is quite an impressive list of purposes and utilization.
So the application of OpenCV Is;
- Image processing Medical Image Analysis is popular because of its many applications.
For example, in identifying brain tumors: Many machines or software are using OpenCV. This helps to detect what stage the tumor is in. It is done by an image segmentation technique.
Also, one of its applications is the RSIP Vision. It builds the probability map to localize the tumor.
- Detecting objects from the images. This is one of the most popular applications.
For example, in traffic or roadway application. You can make a system that detects a person who violates traffic rules.
Such, not wearing a helmet while driving. The system will capture every motorcycle driver who doesn’t wear a helmet.
These are just a few of the many helpful applications of OpenCV.
Reading Image Using OpenCV
Images will be converted into an array of pixels. Moreover, the dimension of images will depend on the resolution.
Also, the computer reads the image as a range of values from 0-225. In addition, color images have 3 primary
- Red
- Green
- Blue
Every primary color is a built-in matrix. Therefore the combination of matrices will provide the value of a pixel.
Resolution are:
- RGB -> (32x32x3 dimensions ->RGB value)
- Grayscale
How Does OpenCV Image Recognition work?
First, build the OpenCV using deep learning. There are two key steps here:
- Applies image recognition so it can detect the location of the face
- Also, embedding the 128-d feature vectors. So that will quantify each face image.
Aligning the face for process
- identifies the geometric structure of the face
- attempts to take an approved alignment of face. It is based on translation, scale, rotation.
Conclusion
OpenCV is the best choice for image recognition and image processing. Also, it is multi-purpose in most of the image-related endeavor.
