Open AccessA Visual Detection and Location Method for Soft Fabrics
Author(s) -
Qiang Gao,
Zhen Li,
Jun Pan
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/612/3/032085
Subject(s) - computer vision , artificial intelligence , canny edge detector , enhanced data rates for gsm evolution , computer science , robot , feature (linguistics) , edge detection , image (mathematics) , image processing , linguistics , philosophy
The soft fabric is prone to burr, fold, enfold and blur, which poses a great challenge to the accuracy of visual edge detection and localization of the autonomous loading and unloading material system of garment robot. In order to overcome the above problems, it proposes an adaptive edge localization method based on double filtering in this paper, which can be used to guide the garment robot to achieve grasping of soft fabric automatically. Firstly, the Gauss filtering and morphological filtering are used to smooth the image, and then it calculates the canny adaptive threshold based on the edge gradient information and detect the edge, finally it locates the coordinates of edge feature extracted. The experiment results show that the method is effective accuracy greater than 96%and robust tested on the real data sets composed of soft fabric. The method has good application value for the autonomous loading and unloading operation of the garment robot and has positive significance for the construction of the intelligent garment factory.