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

• Autorzy: Dourado Antonio Miguel Batista , Pedrino Emerson Carlos

Identyfikatory

DOI

10.15199/48.2020.01.25

Warianty tytułu

PL

Automatyczne generowanie filtru morfologicznego umo˙zliwiaj ˛acego odzyskiwanie brakuj ˛acych danych w systemie wizualizacji i identyfikacji obrazu człowieka

• Języki publikacji: EN

Abstrakty

EN

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.

PL

W artykule zaprezentowano metodę ewolucyjną do automatycznego generowania morfologicznego filtru do określania brakujących danych w obrazach ludzi otrzymywanych on-line. Użyto programu Cartesian Genetic do optymalizacji algorytmu. Zastosowane rozwiązanie umożliwiało dostarczanie poprawę szybkości o dokładności przetwarzania obrazu.

Słowa kluczowe

EN

image processing; real-time embedded system; cartesian genetic programming; multi-objective optimization; assistive technologies

PL

przetwarzanie obrazu; system wbudowany; identyfikacja obrazu

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2020
• Tom: R. 96, nr 1
• Strony: 113--117
• Opis fizyczny: Bibliogr. 28 poz., rys., tab.

Twórcy

autor

Dourado Antonio Miguel Batista

• Federal Institute of São Paulo, Av. Zélia de Lima Rosa - 100, CEP: 18550-000, Boituva-SP, Brazil
• Federal University of São Carlos, Rod. Washington Luís - km 235, CEP: 13565-905, São Carlos-SP, Brazil

autor

Pedrino Emerson Carlos

• Federal University of São Carlos, Rod. Washington Luís - km 235, CEP: 13565-905, São Carlos-SP, Brazil

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).