Naslov
Statistical estimation of the object’s area from the image contaminated with additive noise

Autori
Benšić, Mirta ; Taler, Petar ; Nyarko, Emmanuel Karlo

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
2020 15th Iberian Conference on Information Systems and Technologies (CISTI) / Rocha, Álvaro ; Escobar Peréz, Bernabé ; Peñalvo, Francisco Garcia ; del Mar Miras, Maria ; Gonçalves, Ramiro - Sevilla : Iberian Association for Information Systems and Technologies, 2020, 1-6

ISBN
978-989-54659-0-3

Skup
15th Iberian Conference on Information Systems and Technologies (CISTI'2020)

Mjesto i datum
Sevilla, Španjolska, 24.06.2020. - 27.06.2020

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
circle or ellipse detection, area estimation, noisy image

Sažetak
Area estimation of circular or ellipsoidal object on an image is a current issue in computer vision. Several methods that address this problem have been previously presented, but it turned out that they do not give satisfactory results when dealing with noisy images. As part of the research presented in this paper, a statistical model for estimating the width of uniform distribution for data contaminated with additive error was applied in order to approach the mentioned problem in an innovative manner. Initially, a method for length estimation of intersection of an object with an arbitrary line has been developed. It is possible to estimate the set of object’s edge points using this method. Further, a circle or an ellipse is fitted in that set of points and its area is calculated, which approximates the area of the object itself. It is also possible to estimate the area of a circular or ellipsoidal object represented by a set of points in the plane.The presented method was implemented and publicly released as a package for the programming language R. The method has been extensively tested on the problem of estimating the area of objects recorded using RGB-D camera. Different noise levels were added to the captured images, and estimation results were compared with the ones obtained by several established methods. The test results showed that the method presented in this paper gives qualitatively the best results of area estimation when dealing with noisy images.

Izvorni jezik
Engleski

Znanstvena područja
Matematika, Računarstvo, Informacijske i komunikacijske znanosti

POVEZANOST RADA