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  2. OpenCV - Wikipedia

    en.wikipedia.org/wiki/OpenCV

    OpenCV (Open Source Computer Vision Library) is a library of programming functions mainly for real-time computer vision. [2] Originally developed by Intel , it was later supported by Willow Garage , then Itseez (which was later acquired by Intel [ 3 ] ).

  3. 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]

  4. Foreground detection - Wikipedia

    en.wikipedia.org/wiki/Foreground_detection

    Foreground detection is one of the major tasks in the field of computer vision and image processing whose aim is to detect changes in image sequences. Background subtraction is any technique which allows an image's foreground to be extracted for further processing (object recognition etc.).

  5. Edge detection - Wikipedia

    en.wikipedia.org/wiki/Edge_detection

    The morphological opening operation and the morphological closing operation are applied to the binary image to close gaps. Then, the distance transform operation is applied to the binary image to clear the pixels far from the background, so blob-like shapes or other false labeled regions are deleted from the edge map.

  6. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. [33] Python is dynamically type-checked and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented and functional ...

  7. Bag-of-words model in computer vision - Wikipedia

    en.wikipedia.org/wiki/Bag-of-words_model_in...

    Take a face category and a car category for an example. The face category may emphasize the codewords which represent "nose", "eye" and "mouth", while the car category may emphasize the codewords which represent "wheel" and "window". Given a collection of training examples, the classifier learns different distributions for different categories.

  8. Kernel (image processing) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(image_processing)

    In image processing, a kernel, convolution matrix, or mask is a small matrix used for blurring, sharpening, embossing, edge detection, and more.This is accomplished by doing a convolution between the kernel and an image.

  9. Optical character recognition - Wikipedia

    en.wikipedia.org/wiki/Optical_character_recognition

    Video of the process of scanning and real-time optical character recognition (OCR) with a portable scanner. Optical character recognition or optical character reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene photo (for example the text on signs and ...