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See also
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References
Category:Facebook apps
Category:Internet privacy softwareThe present invention relates generally to digital color image processing, and more particularly to image segmentation utilizing digital signal processing of color image data.
A digital image is a digital representation of an image created through a digital process. Each picture element or pixel in a digital image contains only a single information bit, usually defined as a one or zero, representing the presence or absence of a visual transition at that pixel. This is in contrast to printed images, in which each pixel is represented by a series of light and dark dots, each representing a different visual transition.
Digital images may be processed using computers to allow users to apply special effects to the images and/or select various image features from the digital images. For example, digital images may be processed using digital signal processing of the digital images in a computer.
Most digital images contain color. For example, a digital camera may record colors as represented by digital values in different color spaces. Most images processed using computer technology are of colors. For example, the colors of physical objects, or the colors of the pixels in a digital image, may be represented as digital values, called digital color values.
During image processing, and in the final image output, the image is typically organized into color planes (e.g., red, green, and blue). The color planes are mathematically manipulated to perform various image processing operations on the image (e.g., brightness, contrast, hue, and saturation adjustments). These color planes are also used to store the color information of the digital image.
Image segmentation is the process of reducing an image into color planes (e.g., red, green, and blue) to define image components. Specifically, an image is segmented into three, or more, color planes. Segmentation is also known as clustering or binarization.
Traditional segmentation algorithms may require extensive computing resources and long processing times.
Therefore, it would be beneficial to provide segmentation algorithms that are highly robust and that can be efficiently performed.Natural course of isoniazid-induced choroidal tubercles.
A 26-year-old white male patient with pulmonary tuberculosis had choroidal tubercles and patchy choroidal and optic disc hyperfluorescence. Isoniazid was continued and no laser photocoagulation was performed. Because of its photodynamic nature, laser photocoagulation is recommended
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