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  2. Cropping (image) - Wikipedia

    en.wikipedia.org/wiki/Cropping_(image)

    Cropping is the removal of unwanted outer areas from a photographic or illustrated image. The process usually consists of the removal of some of the peripheral areas of an image to remove extraneous visual data from the picture, improve its framing, change the aspect ratio, or accentuate or isolate the subject matter from its background.

  3. Image geometry correction - Wikipedia

    en.wikipedia.org/wiki/Image_geometry_correction

    Image Geometry Correction onto regular surfaces (such as spheres and cylinders) is the next level of complexity. Both these regular shapes are encountered frequently in Professional Audio Video (Pro AV) situations, in the form of domed or curved wall theatres. Other commonly encountered regular-shaped surfaces are subway walls and pillars.

  4. Valeria Kogan is the CEO of Fermata, a software-development company specializing in agriculture. Her team develops AI tools to reduce crop loss that causes food waste and greenhouse gas emissions.

  5. Computational sustainability - Wikipedia

    en.wikipedia.org/wiki/Computational_Sustainability

    Computer vision is used to monitor crop health, detecting diseases and nutrient deficiencies early. For example, drones equipped with multispectral cameras can capture images of crops, which are then analyzed using machine learning algorithms to identify health issues. Machine learning algorithms can analyze data from sensors and drones to ...

  6. Image rectification - Wikipedia

    en.wikipedia.org/wiki/Image_rectification

    Computer stereo vision takes two or more images with known relative camera positions that show an object from different viewpoints. For each pixel it then determines the corresponding scene point's depth (i.e. distance from the camera) by first finding matching pixels (i.e. pixels showing the same scene point) in the other image(s) and then ...

  7. Features from accelerated segment test - Wikipedia

    en.wikipedia.org/wiki/Features_from_accelerated...

    The compiled code is used as corner detector later for other images. Notice that the corners detected using this decision tree algorithm should be slightly different from the results using segment test detector. This is because that decision tree model depends on the training data, which could not cover all possible corners.

  8. Harris corner detector - Wikipedia

    en.wikipedia.org/wiki/Harris_corner_detector

    The Harris corner detector is a corner detection operator that is commonly used in computer vision algorithms to extract corners and infer features of an image. It was first introduced by Chris Harris and Mike Stephens in 1988 upon the improvement of Moravec's corner detector . [ 1 ]

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