A comparative study of multi-sensor data fusion methods for highly accurate assessment of manufactured parts

Ammar Hannachi; Sophie Kohler; Alex Lallement; Ernest Hirsch

doi:10.1117/12.2182832

30 April 2015 A comparative study of multi-sensor data fusion methods for highly accurate assessment of manufactured parts

Ammar Hannachi, Sophie Kohler, Alex Lallement, Ernest Hirsch

Author Affiliations +

Proceedings Volume 9534, Twelfth International Conference on Quality Control by Artificial Vision 2015; 95340X (2015) https://doi.org/10.1117/12.2182832
Event: The International Conference on Quality Control by Artificial Vision 2015, 2015, Le Creusot, France

Abstract

3D modeling of scene contents takes an increasing importance for many computer vision based applications. In particular, industrial applications of computer vision require efficient tools for the computation of this 3D information. Routinely, stereo-vision is a powerful technique to obtain the 3D outline of imaged objects from the corresponding 2D images. As a consequence, this approach provides only a poor and partial description of the scene contents. On another hand, for structured light based reconstruction techniques, 3D surfaces of imaged objects can often be computed with high accuracy. However, the resulting active range data in this case lacks to provide data enabling to characterize the object edges. Thus, in order to benefit from the positive points of various acquisition techniques, we introduce in this paper promising approaches, enabling to compute complete 3D reconstruction based on the cooperation of two complementary acquisition and processing techniques, in our case stereoscopic and structured light based methods, providing two 3D data sets describing respectively the outlines and surfaces of the imaged objects. We present, accordingly, the principles of three fusion techniques and their comparison based on evaluation criterions related to the nature of the workpiece and also the type of the tackled application. The proposed fusion methods are relying on geometric characteristics of the workpiece, which favour the quality of the registration. Further, the results obtained demonstrate that the developed approaches are well adapted for 3D modeling of manufactured parts including free-form surfaces and, consequently quality control applications using these 3D reconstructions.

Citation Download Citation

Ammar Hannachi, Sophie Kohler, Alex Lallement, and Ernest Hirsch "A comparative study of multi-sensor data fusion methods for highly accurate assessment of manufactured parts", Proc. SPIE 9534, Twelfth International Conference on Quality Control by Artificial Vision 2015, 95340X (30 April 2015); https://doi.org/10.1117/12.2182832

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
8 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Structured light

Data fusion

3D modeling

Sensors

3D image processing

3D vision

Head

Show All Keywords

Keywords/Phrases

Search In:

Publication Years