|Autors: KOUNTCHEV, R. K., RUBIN,S., MILANOVA,M., TODOROV,V., KOUNTCHEVA,R.|
Title: Cognitive Image Representation Based on Spectrum Pyramid Decomposition
Keywords: Cognitive image representation, Image decomposition
Abstract: The contemporary image representation is based on various techniques, using matrices, vectors, multi-resolution pyramids, R-tree, orthogonal transforms, anisotropic perceptual representations, etc. In this paper is offered one new approach for cognitive image representation based on adaptive spectrum pyramid decomposition controlled by neural networks. This approach corresponds to the hypothesis of the human way for image recognition using consecutive approximations with increasing resolution for the selected regions of interest. Such image representation is suitable for the creation of the objects’ learning models, which should be extracted from image databases in accordance with predefined decision rules. Significant element of the new representation is the use of a feedback, which to provide iterative change of the cognitive models’ parameters in accordance with the data mining results obtained.
Вид: публикация в национален форум
Въведена от: ас. Ана Георгиева Пискова