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  2. Distance transform - Wikipedia

    en.wikipedia.org/wiki/Distance_transform

    A distance transform, also known as distance map or distance field, is a derived representation of a digital image.The choice of the term depends on the point of view on the object in question: whether the initial image is transformed into another representation, or it is simply endowed with an additional map or field.

  3. Hausdorff distance - Wikipedia

    en.wikipedia.org/wiki/Hausdorff_distance

    In computer vision, the Hausdorff distance can be used to find a given template in an arbitrary target image. The template and image are often pre-processed via an edge detector giving a binary image. Next, each 1 (activated) point in the binary image of the template is treated as a point in a set, the "shape" of the template.

  4. Fréchet inception distance - Wikipedia

    en.wikipedia.org/wiki/Fréchet_inception_distance

    The Fréchet inception distance (FID) is a metric used to assess the quality of images created by a generative model, like a generative adversarial network (GAN) [1] or a diffusion model. [2] [3] The FID compares the distribution of generated images with the distribution of a set of real images (a "ground truth" set).

  5. Scale-invariant feature transform - Wikipedia

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

    SIFT keypoints of objects are first extracted from a set of reference images [1] and stored in a database. An object is recognized in a new image by individually comparing each feature from the new image to this database and finding candidate matching features based on Euclidean distance of their feature vectors. From the full set of matches ...

  6. Mathematical morphology - Wikipedia

    en.wikipedia.org/wiki/Mathematical_morphology

    Mathematical morphology (MM) is a theory and technique for the analysis and processing of geometrical structures, based on set theory, lattice theory, topology, and random functions. MM is most commonly applied to digital images , but it can be employed as well on graphs , surface meshes , solids , and many other spatial structures.

  7. Similarity measure - Wikipedia

    en.wikipedia.org/wiki/Similarity_measure

    An image distance measure compares the similarity of two images in various dimensions such as color, texture, shape, and others. For example, a distance of 0 signifies an exact match with the query, with respect to the dimensions that were considered. As one may intuitively gather, a value greater than 0 indicates various degrees of ...

  8. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    Wikipedia-based Image Text Dataset 37.5 million image-text examples with 11.5 million unique images across 108 Wikipedia languages. 11,500,000 image, caption Pretraining, image captioning 2021 [7] Srinivasan e al, Google Research Visual Genome Images and their description 108,000 images, text Image captioning 2016 [8] R. Krishna et al.

  9. DBSCAN - Wikipedia

    en.wikipedia.org/wiki/DBSCAN

    The quality of DBSCAN depends on the distance measure used in the function regionQuery(P,ε). The most common distance metric used is Euclidean distance. Especially for high-dimensional data, this metric can be rendered almost useless due to the so-called "Curse of dimensionality", making it difficult to find an appropriate value for ε. This ...