Image Processing

Image processing techniques are by definition tools used to modify the contents of an image so they satisfy a particular set of requirements or conditions.

Traditional examples of this kind of tools are: Putting the finishing touches on artificially generated images, improving images obtained through different input devices, implementing pattern recognition (both for natural ones such as faces, and artificial ones such as symbols and logotypes), or filtering data. Thanks to the variety of challenges and projects Zooloop has faced, the company has an arsenal of techniques, tools, algorithms and libraries to implement a great number of image processing techniques, such as:


Face Tracking
Face Tracking


  • Color Constancy: To obtain uniform images, independently of lightning conditions and input devices.
  • Face Tracking: To detect and follow faces in still images or video feeds.
  • Image Smoothing: To soften borders and eliminate noise from depth cameras.





  • Color Space Transformations: To better detect certain features in images that can’t be accurately represented by using certain paradigms of digital color representation.
  • Segmentation: To detect borders and objects in an image.
  • Optical Flow: To detect movement between video frames.

Segmentation

Alpha Matting


  • Brightness, Contrast and Levels adjustments: To change the way colours are shown in images.
  • Background Subtraction: To extract an element from an image, so it’s possible to include it into a completely different scene. This technique can be applied to still images and videos.
  • Alpha Matting: To mix two images by making sections of one of them transparent.



Videos


Face Tracking

Segmentation


Alpha Matting


Related Projects

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