Open Source Computer Vision Library or OpenCV is an extraordinary library of multimedia resources. What are its uses and for what purposes are they used?
Computer Vision: Definition
It is essential to first understand what computer vision is. The computer vision allows us to capture images and videos. Are therefore included in this process: their storage procedure, extraction and treatment of all kinds. artificial intelligence (AI) originates from computer vision. These operations are fundamental in robotics, in automatic driving and in the processing of photographic images.
OpenCV: What is it?
OpenCV is an imperative requirement in the process of computer vision, machine learning and image manipulation. Indeed, it is a big open-source library images and videos. In English, OpenCV responds to the acronym of Open Source Computer Vision Library.
Thanks to it, real-time operation is accessible. By exploiting the images, the videos, we arrive at determine the identity of recognized facesof the objects until manuscripts.
Its combination with other libraries expands the possible functionalities. Integrated with Numpy of Python, it makes it possible to exploit the structure of the OpenCV table to facilitate its analysis. The tools used to identify images, their patterns, their characteristics are vector space, mathematical calculations.
Intel Research had taken the initiative in 1999 to launch OpenCV. The company wanted, at this time, to evolve applications that were CPU-intensive. At the conceptual head of this application were many optimization experts from Intel Russia. On the other hand, the members responsible for the performance library were also part of the design team.
In 2012, OpenCV changed hands and became OpenCV.org when a non-profit foundation decided to buy it. This foundation was already working in a development site.
In 2016, Intel will sign a contract to appropriate Itseez, one of its fundamental developers.
In 2020, things have evolved, OpenCV launches Kickstarter for OpenCVAI. This will be a range of hardware added to the library to harness space-based artificial intelligence.
OpenCV 1.0: what are the characteristics of this version?
There was a first version named OpenCV 1.0published under BSD license. This version was free of charge and was used mainly for commercial or educational purposes. It operated Windows, Linux, MAC PS, iOS and Android systems. As interfaces: C++, C, Python and Java were available. As computer languages used, C and C++ were favored to take advantage of multicore.
Applications that take advantage of OpenCV
The OpenCV apps paved the way for many other applications. We can cite: the facial recognitionautomatic surveillance systems, the census of people in a given place, vehicles and their speed on highways, artistic platforms.
Thanks to OpenCV, we can easily detect certain defects in the manufacturing cycle of certain products. OpenCV streamlines the exploitation of images street viewsearching and retrieving media files as well as medical image analysis. In 3D movies, she can define structure by studying motion.
What are the features of OpenCV?
OpenCV features mostly boil down to image processing, object and feature detection, machine learning, and CUDA acceleration.
OpenCV is its open source name. He is qualified for the speed of his treatment and his prototype. Its ease of integration and coding are some of its popular features.
By image processing, we mean all possible operations on a given image. The objective is to improve its quality or extract hidden information. To go further, an image can be represented in an orthonormal dimension. It could respond to the function f(x, y). “x” and “y” at this time would be its coordinates. The gray level corresponds to the amplitude of the fatness of the pairs of coordinates (x, y). This function determines the pixel value of the image, which will in turn establish its brightness and color.
This treatment involves three specific steps: import, analysis and/or manipulation and finally output. The output can be either an output image or a report resulting from the analysis of the image.
OpenCV also provides some graphical interface functions. Thanks to the application, one can also insert texts in an image, use sliders and controls associated with the mouse.
In sum, OpenCV handles almost all classic image-based operations. These are the reading, display, thresholding, smoothing and filtering, segmentation and mathematical morphology of an image.
How can a machine recognize or read a certain image?
The computer does not respond consistently to a spontaneous request such as “Is that me in the picture?” “. However, it performs an internal mathematical calculation by reading the given image under a range of values between 0 and 255. And these analyzed values allow the recognition of a certain face. For colors, the analysis goes through three primary channels: red, blue and green.
What could be the alternatives to OpenCV?
If we cannot appropriate it, we can have recourse to a dozen alternatives. Like for example, Microsoft Computer Vision API, Azure Face API, Cloud Vision API, Amazon Recognition, G2 offers, scikit-image, SimpleCV, Clarifi’s, DeepPy, IBM Watson.
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OpenCV: focus on the open source library – LeBigData.fr
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