Отрывок: Figure 1b shows the dependences of computational complexity on the object size w = l at a constant image size W = L = 1024 and with the same methodical charac- teristics. One can see that the computational complexity of CAM, SGI, and CEA depends weakly on object size in the frequency region, and that for the CEA it is approxi- mately quadratic in the spatial region. The SGI with the MSFD requires a ...
Название : Efficiency of object identification for binary images
Авторы/Редакторы : Magdeev, R.
Tashlinskii, Al.
Ключевые слова : digital image
object recognition
pattern recognition
correlation-extreme algorithm
stochastic gradient identification
incorrect identification probability
Дата публикации : Апр-2019
Издательство : Новая техника
Библиографическое описание : Magdeev RG, Tashlinskii AG. Efficiency of object identification for binary images. Computer Optics 2019; 43(2): 277-281. DOI: 10.18287/2412-6179-2019-43-2-277-281.
Серия/номер : 43;2
Аннотация : In this paper, a comparative analysis of the correlation-extreme method, the method of contour analysis and the method of stochastic gradient identification in the objects identification for a binary image is carried out. The results are obtained for a situation where possible deformations of an identified object with respect to a pattern can be reduced to a similarity model, that is, the pattern and the object may differ in scale, orientation angle, shift along the base axes, and additive noise. The identification of an object is understood as the recognition of its image with an estimate of the strain parameters relative to the template.
URI (Унифицированный идентификатор ресурса) : https://dx.doi.org/10.18287/2412-6179-2019-43-2-277-281
http://repo.ssau.ru/handle/Zhurnal-Komputernaya-optika/Efficiency-of-object-identification-for-binary-images-77079
Другие идентификаторы : Dspace\SGAU\20190524\77079
Располагается в коллекциях: Журнал "Компьютерная оптика"

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