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What is an OpenCV?

OpenCV or Open Source Computer Vision Library is a cross-platform library, which is concerned with video capture, video processing, and analysis. It comprises features, which support object and face detection. It can be used for developing real-time computer applications. OpenCV is a large open-source library used for machine learning, computer vision, and image processing. 

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OpenCV plays a significant role in the real-time operation that is vital in today’s systems. If you use it, you can process videos and images for identifying faces, objects, or handwriting of humans. If it is integrated with different libraries including Numpuy, python can process an OpenCV array structure needed for analysis.

For identifying image patterns and different features, you can use vector space for performing mathematical operations. We offer OpenCV assignment help at the best industry rates so that they are affordable to all students regardless of their financial position. 

The Applications of OpenCV

There are a lot of applications that are solved with OpenCV. The applications are listed in our OpenCV homework help service as follows:

  • face recognition
  • Interactive art installations
  • Number of counts
  • Automated surveillance and inspection
  • Medical image analysis
  • Vehicle counting on the highways with speeds
  • object recognition
  • Anamoly detection in a manufacturing process
  • Movies 3D structure
  • TV advertisement recognition
  • Image/video search as well as retrieval
  • Driver-less and robot car navigation

What are the Library Modules of OpenCV?

The library modules are discussed in our OpenCV assignment help:

  1. Core Functionality: The basic data structures such as range, scalar, and point are included in this module. These are data structures, which are used for buildings in OpenCV. The main functionality module involves a Multidimensional array or Mat that is used for storing the images. The model is a part of the package under org.OpenCV.core in a Java library.
  2. Image Processing Module: This module has the responsibility for many image processing operations, which include image filtering, geometrical image transformations, colour space conversion, histogram, etc. This module is a part of a package under org.OpenCV.imgproc in a Java library.
  3. Video Module: In this module, the video analysis concepts including object tracking, motion estimation, and background estimations are performed.
  4. Video I/O: It uses the OpenCV library for explaining video codecs and capturing.
  5. Cali3d: This module comprises algorithms regarding multiple-view geometry, object pose estimation, single and stereo camera, 3D reconstruction elements, object pose estimation, and stereo correspondence.
  6. Features2D: This module has the concepts of feature description and detection.

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The Features of OpenCV

The features are highlighted in our quality assignment writing help with OpenCV:

  • Save and capture videos
  • Read as well as write images
  • Performing feature detection
  • Processing images
  • Detecting specific objects like eyes, face, cars in images and videos
  • Analyzing the videos

OpenCV was developed originally in C++. It runs on different operating systems including Linux, Windows, FreeBSD, Osx, Open BSD, Net BSD, etc.

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