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This extraction may involve quite considerable amounts of image processing. The result is known as a feature descriptor or feature vector. Among the approaches that are used to feature description, one can mention N-jets and local histograms (see scale-invariant feature transform for one example of a local histogram descriptor). In addition to ...
In computer vision, visual descriptors or image descriptors are descriptions of the visual features of the contents in images, videos, or algorithms or applications that produce such descriptions. They describe elementary characteristics such as the shape , the color , the texture or the motion , among others.
A re-cut is a type of feature. In archaeological excavation, a feature is a collection of one or more contexts representing some human non-portable activity, such as a hearth or wall. [1] Features serve as an indication that the area in which they are found has been interfered with in the past, usually by humans. [2]
Attributes, characteristics of a feature other than location, often expressed as text or numbers; for example, the population of a city. [19] In geography, the levels of measurement developed by Stanley Smith Stevens (and further extended by others) is a common system for understanding and using attribute data.
The detection and description of local image features can help in object recognition. The SIFT features are local and based on the appearance of the object at particular interest points, and are invariant to image scale and rotation. They are also robust to changes in illumination, noise, and minor changes in viewpoint.
Artificial texture example. Natural texture example. An image texture is the small-scale structure perceived on an image, based on the spatial arrangement of color or intensities. [1] It can be quantified by a set of metrics calculated in image processing. Image texture metrics give us information about the whole image or selected regions. [1]
In feature engineering, two types of features are commonly used: numerical and categorical. Numerical features are continuous values that can be measured on a scale. Examples of numerical features include age, height, weight, and income. Numerical features can be used in machine learning algorithms directly. [citation needed]
Distinctive features have also been used to distinguish proverbs from other types of language such as slogans, clichés, and aphorisms. [10] Analogous feature systems are also used throughout Natural Language Processing (NLP). For example, part-of-speech tagging divides words into categories. These include "major" categories such as Noun vs ...