Open AccessSubjective modeling of image shape
Author(s) -
A. I. Chulichkov
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1368/3/032027
Subject(s) - measure (data warehouse) , image (mathematics) , set (abstract data type) , artificial intelligence , computer science , function (biology) , likelihood function , computer vision , pattern recognition (psychology) , mathematics , algorithm , data mining , estimation theory , evolutionary biology , biology , programming language
The paper presents two approaches to subjective modelling incomplete and uncertain information about possible shape of images. The shape is understood as a set of images of the scene, recorded under all possible conditions (lighting, exposure, etc.). To simulate the likelihood, the measure of likelihood introduced by Yu.P. Pytyev is used. This measure is a function defined on a set of statements and ordering them according to plausibility. The obtained subjective models of shapes allow using the theory of optimal strategies for solving morphological problems.