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  2. Feature (computer vision) - Wikipedia

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

    When feature extraction is done without local decision making, the result is often referred to as a feature image. Consequently, a feature image can be seen as an image in the sense that it is a function of the same spatial (or temporal) variables as the original image, but where the pixel values hold information about image features instead of ...

  3. Feature engineering - Wikipedia

    en.wikipedia.org/wiki/Feature_engineering

    Feature engineering in machine learning and statistical modeling involves selecting, creating, transforming, and extracting data features. Key components include feature creation from existing data, transforming and imputing missing or invalid features, reducing data dimensionality through methods like Principal Components Analysis (PCA), Independent Component Analysis (ICA), and Linear ...

  4. Scale-invariant feature transform - Wikipedia

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

    FBM models the image probabilistically as a collage of independent features, conditional on image geometry and group labels, e.g. healthy subjects and subjects with Alzheimer's disease (AD). Features are first extracted in individual images from a 4D difference of Gaussian scale-space, then modeled in terms of their appearance, geometry and ...

  5. Local binary patterns - Wikipedia

    en.wikipedia.org/wiki/Local_binary_patterns

    The LBP feature vector, in its simplest form, is created in the following manner: Divide the examined window into cells (e.g. 16x16 pixels for each cell). For each pixel in a cell, compare the pixel to each of its 8 neighbors (on its left-top, left-middle, left-bottom, right-top, etc.).

  6. Hough transform - Wikipedia

    en.wikipedia.org/wiki/Hough_transform

    The Hough transform is a feature extraction technique used in image analysis, computer vision, pattern recognition, and digital image processing. [1] [2] The purpose of the technique is to find imperfect instances of objects within a certain class of shapes by a voting procedure.

  7. Gabor filter - Wikipedia

    en.wikipedia.org/wiki/Gabor_filter

    In document image processing, Gabor features are ideal for identifying the script of a word in a multilingual document. [13] Gabor filters with different frequencies and with orientations in different directions have been used to localize and extract text-only regions from complex document images (both gray and colour), since text is rich in ...

  8. List of datasets in computer vision and image processing

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

    10 billion pairs of alt-text and image sources in HTML documents in CommonCrawl 746,972,269 Images, Text Classification, Image-Language 2022 [31] SIFT10M Dataset SIFT features of Caltech-256 dataset. Extensive SIFT feature extraction. 11,164,866 Text Classification, object detection 2016 [32] X. Fu et al. LabelMe: Annotated pictures of scenes.

  9. CVIPtools - Wikipedia

    en.wikipedia.org/wiki/CVIPtools

    The Computer Vision and Image Processing Feature Extraction and Pattern Classification Tool, CVIP-FEPC, is used to advance human and computer vision applications. While its primary function is computer vision, it serves various purposes, such as supporting the development of image compression schemes for human vision applications by identifying ...