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  2. Digital image processing - Wikipedia

    en.wikipedia.org/wiki/Digital_image_processing

    Digital image processing is the use of a digital computer to process digital images through an algorithm. [ 1 ] [ 2 ] As a subcategory or field of digital signal processing , digital image processing has many advantages over analog image processing .

  3. Pruning (morphology) - Wikipedia

    en.wikipedia.org/wiki/Pruning_(morphology)

    The pruning algorithm is a technique used in digital image processing based on mathematical morphology. [1] It is used as a complement to the skeleton and thinning algorithms to remove unwanted parasitic components (spurs). In this case 'parasitic' components refer to branches of a line which are not key to the overall shape of the line and ...

  4. Neighborhood operation - Wikipedia

    en.wikipedia.org/wiki/Neighborhood_operation

    In computer vision and image processing a neighborhood operation is a commonly used class of computations on image data which implies that it is processed according to the following pseudo code: Visit each point p in the image data and do { N = a neighborhood or region of the image data around the point p result(p) = f(N) }

  5. 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.

  6. Scale-invariant feature transform - Wikipedia

    en.wikipedia.org/wiki/Scale-invariant_feature...

    For scale space extrema detection in the SIFT algorithm, the image is first convolved with Gaussian-blurs at different scales. The convolved images are grouped by octave (an octave corresponds to doubling the value of σ {\displaystyle \sigma } ), and the value of k i {\displaystyle k_{i}} is selected so that we obtain a fixed number of ...

  7. Split and merge segmentation - Wikipedia

    en.wikipedia.org/wiki/Split_and_merge_segmentation

    There are several ways to define homogeneity, some examples are: Uniformity- the region is homogeneous if its gray scale levels are constant or within a given threshold. Local mean vs global mean - if the mean of a region is greater than the mean of the global image, then the region is homogeneous; Variance - the gray level variance is defined as

  8. Gabor filter - Wikipedia

    en.wikipedia.org/wiki/Gabor_filter

    Its impulse response is defined by a sinusoidal wave (a plane wave for 2D Gabor filters) multiplied by a Gaussian function. [6] Because of the multiplication-convolution property (Convolution theorem), the Fourier transform of a Gabor filter's impulse response is the convolution of the Fourier transform of the harmonic function (sinusoidal function) and the Fourier transform of the Gaussian ...

  9. Image analysis - Wikipedia

    en.wikipedia.org/wiki/Image_analysis

    Image analysis or imagery analysis is the extraction of meaningful information from images; mainly from digital images by means of digital image processing techniques. [1] Image analysis tasks can be as simple as reading bar coded tags or as sophisticated as identifying a person from their face .