Czasopismo | PRZEGLĄD ELEKTROTECHNICZNY | Rocznik 2020 - zeszyt 1

Automatic generation of high performance morphological filters to fix missing data in depth images on real-time embedded systems for visually impaired people

Automatyczne generowanie filtru morfologicznego umoz˙liwiaja˛cego odzyskiwanie brakuja˛cych danych w systemie wizualizacji i identyfikacji obrazu człowieka

10.15199/48.2020.01.25

nr katalogowy: 124185
10.15199/48.2020.01.25

Streszczenie

The paper presents an evolutionary multi-objective approach to automatically generate morphological filters to solve unknown distances areas, found in depth images used by real-time embedded systems for visually impaired people, and to prevent accidents. It was used Cartesian Genetic Programming as base for the NSGAII multi-objective optimization algorithm proposed to optimize two objectives: low error rates for quality x low complexity for speed. Results showed this approach was able to deliver feasible solutions with good quality and speed to be used in real-time systems.

Abstract

W artykule zaprezentowano metode˛ ewolucyjna˛ do automatycznego generowania morfologicznego filtru do okres´lania brakuja˛cych danych w obrazach ludzi otrzymywanych on-line. Uz˙yto programu Cartesian Genetic do optymalizacji algorytmu. Zastosowane rozwia˛zanie umoz˙liwiało dostarczanie poprawe˛ szybkos´ci o dokładnos´ci przetwarzania obrazu.

Słowa kluczowe

Keywords

Bibliografia

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