Computer Vision And High Level Vision Essay

843 Words Feb 23rd, 2016 4 Pages
Computer Vision is commonly studied in three categories according to the degree of abstraction from the image: low-level, mid-level, and high-level. Low-level vision focuses on mapping pixel to pixel, which is best for detecting edges and features. Mid-level vision maps pixels to regions, which is used to detect three dimensional structures from motion. High-level vision maps pixels and regions to abstract categories (Huttenlocher, n.d.). In regards to human vision, images travel to the lateral geniculate nucleus(LGN), which separates the image into 2 parallel streams, the parvocellular layers containing color and fine structure, and the magnocellular layers containing contrast and motion. The parvocellular mirrors low-level vision by detecting specific colors and acute structures while the magnocellular layers mirror mid-level vision by detecting regions and structures from contrast in motion (How Vision Works, 2015). The way in which the brain interprets this information is homologous with high-level vision. Both interpretations separate the image into subcategories that allow for the distinguishing of abstract information. These similarities all suggest that computer vision is derived from human vision alone. The process of separating an image into levels is a synthetic form of the parvocellular and magnocellular layers in human vision.
OpenCV is a computer vision application program interface (API) originally made open source as an Intel Research initiative to advance…

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