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  2. Template matching - Wikipedia

    en.wikipedia.org/wiki/Template_matching

    For example, if an algorithm is looking for a face, its template eigenspaces may consist of images (i.e., templates) of faces in different positions to the camera, in different lighting conditions, or with different expressions (i.e., poses). It is also possible for a matching image to be obscured or occluded by an object.

  3. Facial recognition system - Wikipedia

    en.wikipedia.org/wiki/Facial_recognition_system

    Facial recognition software at a US airport Automatic ticket gate with face recognition system in Osaka Metro Morinomiya Station. A facial recognition system [1] is a technology potentially capable of matching a human face from a digital image or a video frame against a database of faces.

  4. Scale-invariant feature transform - Wikipedia

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

    The hash table is searched to identify all clusters of at least 3 entries in a bin, and the bins are sorted into decreasing order of size. Each of the SIFT keypoints specifies 2D location, scale, and orientation, and each matched keypoint in the database has a record of its parameters relative to the training image in which it was found.

  5. Speeded up robust features - Wikipedia

    en.wikipedia.org/wiki/Speeded_up_robust_features

    Accordingly, the scale space is analyzed by up-scaling the filter size rather than iteratively reducing the image size. The output of the above 9×9 filter is considered as the initial scale layer at scale s =1.2 (corresponding to Gaussian derivatives with σ = 1.2).

  6. Viola–Jones object detection framework - Wikipedia

    en.wikipedia.org/wiki/Viola–Jones_object...

    F(0) = 1.0; D(0) = 1.0; i = 0 while F(i) > Ftarget increase i n(i) = 0; F(i)= F(i-1) while F(i) > f × F(i-1) increase n(i) use P and N to train a classifier with n(i) features using AdaBoost Evaluate current cascaded classifier on validation set to determine F(i) and D(i) decrease threshold for the ith classifier (i.e. how many weak ...

  7. Comparison of image viewers - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_image_viewers

    Yes Filenames, file creation/modification date, Exif date taken, GPS timestamp FastStone Image Viewer: Yes Yes Yes 1:1, 2%-5000% magnifier, click-and-hold zooming, fit width and/or height, lock No Yes 6 predefined sizes Yes database dir-tree, back and forth navigation, bookmarks Yes Yes user-defined, name, date, file size, image size, type ...

  8. Feature (computer vision) - Wikipedia

    en.wikipedia.org/wiki/Feature_(computer_vision)

    For example, an edge can be represented as a Boolean variable in each image point that describes whether an edge is present at that point. Alternatively, we can instead use a representation that provides a certainty measure instead of a Boolean statement of the edge's existence and combine this with information about the orientation of the edge.

  9. Approximate string matching - Wikipedia

    en.wikipedia.org/wiki/Approximate_string_matching

    With the availability of large amounts of DNA data, matching of nucleotide sequences has become an important application. [1] Approximate matching is also used in spam filtering. [5] Record linkage is a common application where records from two disparate databases are matched. String matching cannot be used for most binary data, such as images ...