enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Harris corner detector - Wikipedia

    en.wikipedia.org/wiki/Harris_corner_detector

    In order to capture the corners from the image, researchers have proposed many different corner detectors including the Kanade-Lucas-Tomasi (KLT) operator and the Harris operator which are most simple, efficient and reliable for use in corner detection. These two popular methodologies are both closely associated with and based on the local ...

  3. Co-occurrence matrix - Wikipedia

    en.wikipedia.org/wiki/Co-occurrence_matrix

    A co-occurrence matrix or co-occurrence distribution (also referred to as : gray-level co-occurrence matrices GLCMs) is a matrix that is defined over an image to be the distribution of co-occurring pixel values (grayscale values, or colors) at a given offset. It is used as an approach to texture analysis with various applications especially in ...

  4. Caltech 101 - Wikipedia

    en.wikipedia.org/wiki/Caltech_101

    Due to its open nature, LabelMe has many more images covering a much wider scope than Caltech 101. However, since each person decides what images to upload, and how to label and annotate each image, the images are less consistent. VOC 2008 is a European effort to collect images for benchmarking visual categorization methods.

  5. Connected-component labeling - Wikipedia

    en.wikipedia.org/wiki/Connected-component_labeling

    In order to do that a linked list is formed that will keep the indexes of the pixels that are connected to each other, steps (2) and (3) below. The method of defining the linked list specifies the use of a depth or a breadth first search. For this particular application, there is no difference which strategy to use.

  6. Normalization (image processing) - Wikipedia

    en.wikipedia.org/wiki/Normalization_(image...

    max is the maximum value for color level in the input image within the selected kernel. min is the minimum value for color level in the input image within the selected kernel. [4] Local contrast stretching considers each range of color palate in the image (R, G, and B) separately, providing a set of minimum and maximum values for each color palate.

  7. Quantization (image processing) - Wikipedia

    en.wikipedia.org/wiki/Quantization_(image...

    This technique is commonly used for simplifying images, reducing storage requirements, and facilitating processing operations. In grayscale quantization, an image with N intensity levels is converted into an image with a reduced number of levels, typically L levels, where L<N. The process involves mapping each pixel's original intensity value ...

  8. Histogram equalization - Wikipedia

    en.wikipedia.org/wiki/Histogram_equalization

    For example, if applied to 8-bit image displayed with 8-bit gray-scale palette it will further reduce color depth (number of unique shades of gray) of the image. Histogram equalization will work the best when applied to images with much higher color depth than palette size, like continuous data or 16-bit gray-scale images.

  9. Thresholding (image processing) - Wikipedia

    en.wikipedia.org/wiki/Thresholding_(image...

    Object Attribute-based methods search a measure of similarity between the gray-level and the binarized images, such as fuzzy shape similarity, edge coincidence, etc., Spatial methods use higher-order probability distribution and/or correlation between pixels. Example of the advantage of local thresholding in the case of inhomogeneous lighting.