Concept
Opening (morphology)
Concepts associés (6)
Dilation (morphology)
Dilation (usually represented by ⊕) is one of the basic operations in mathematical morphology. Originally developed for , it has been expanded first to grayscale images, and then to complete lattices. The dilation operation usually uses a structuring element for probing and expanding the shapes contained in the input image. In binary morphology, dilation is a shift-invariant (translation invariant) operator, equivalent to Minkowski addition. A binary image is viewed in mathematical morphology as a subset of a Euclidean space Rd or the integer grid Zd, for some dimension d.
Closing (morphology)
In mathematical morphology, the closing of a set () A by a structuring element B is the erosion of the dilation of that set, where and denote the dilation and erosion, respectively. In , closing is, together with opening, the basic workhorse of morphological noise removal. Opening removes small objects, while closing removes small holes. It is idempotent, that is, . It is increasing, that is, if , then . It is extensive, i.e., . It is translation invariant.
Structuring element
In mathematical morphology, a structuring element is a shape, used to probe or interact with a given image, with the purpose of drawing conclusions on how this shape fits or misses the shapes in the image. It is typically used in morphological operations, such as dilation, erosion, opening, and closing, as well as the hit-or-miss transform. According to Georges Matheron, knowledge about an object (e.g., an image) depends on the manner in which we probe (observe) it.
Érosion (informatique)
L'érosion est l'une des deux opérations fondamentales du traitement d'image morphologique. Soit A une image binaire, respectant les conventions usuelles suivantes : Les pixels ayant la valeur 0 sont considérés de couleur noire et représentent le fond. Les pixels ayant la valeur 1 sont considérés de couleur blanche et représentent le sujet de l'image. Soit B un élément structurant, respectant lui aussi ces conventions.
Morphologie mathématique
La morphologie mathématique est une théorie et technique mathématique et informatique d'analyse de structures qui est liée avec l'algèbre, la théorie des treillis, la topologie et les probabilités. Le développement de la morphologie mathématique est inspiré des problèmes de , domaine qui constitue son principal champ d'application. Elle fournit en particulier des outils de filtrage, , quantification et modélisation d'images. Elle est également utilisable en traitement du signal, par exemple pour filtrer les variations d'une mesure (physique, biologique) au cours du temps.
Digital image processing
Digital image processing is the use of a digital computer to process s through an algorithm. As a subcategory or field of digital signal processing, digital image processing has many advantages over . It allows a much wider range of algorithms to be applied to the input data and can avoid problems such as the build-up of noise and distortion during processing. Since images are defined over two dimensions (perhaps more) digital image processing may be modeled in the form of multidimensional systems.