Štetje objektov na slikah z uporabo genetskega algoritma

BABNIK, GREGOR (author), Šajn, Luka (mentor)

Delo obravnava način samodejnega štetja objektov na slikah. Uporabljena metoda za učenje je genetski algoritem, s katerim se išče zaporedje ustreznih operacij, ki se jih nato izvede nad podanimi slikami. Uspešnost posamezne rešitve se meri z odstopanjem med številoma preštetih in dejanskih objektov. Za nastavitev ločljivosti vhodnih slik se uporablja algoritem ARes. Implementacija procesiranja slik se izvaja z uporabo programskih knjižnic Tensorflow in OpenCV. Delo je testirano na množicah slik iz različnih domen.

• Language: Slovenian
• Keywords: štetje, genetski algoritem, tensorflow, opencv, ares
• Work type: Bachelor thesis/paper
• Typology: 2.11 - Undergraduate Thesis
• Organization: FRI - Faculty of Computer and Information Science
• Year: 2020
• PID: 20.500.12556/RUL-117266
• COBISS.SI-ID: 21798403
• Publication date in RUL: 03.07.2020

Secondary language

• Language: English
• Title: Counting objects in images using a genetic algorithm

Abstract

The work deals with the automatic counting of objects in images. A genetic algorithm is used as a learning method to find appropriate operations used to process the images. The success of an individual solution is measured as a difference between the number of counted objects and the real object count. ARes algorithm is used to adjust the resolution of input images. The image processing part is implemented using two libraries TensorFlow and OpenCV. The work is tested against various sets of images in different domains.

• Keywords: counting, genetic algorithm, tensorflow, opencv, ares