학술논문

Defects Detection in Highly Specular Surface using a Combination of Stereo and Laser Reconstruction
Document Type
Conference
Source
2020 35th International Conference on Image and Vision Computing New Zealand (IVCNZ) Image and Vision Computing New Zealand (IVCNZ), 2020 35th International Conference on. :1-6 Nov, 2020
Subject
Computing and Processing
Signal Processing and Analysis
Surface reconstruction
Three-dimensional displays
Lighting
Surface emitting lasers
Inspection
Image reconstruction
Surface treatment
Defects Detection
Reflective Surface
3D Reconstruction
Laser Line Projection
Stereo Vision
Language
ISSN
2151-2205
Abstract
Product inspection is an indispensable tool of the current manufacturing process. It helps maintain the quality of the product and reduces manufacturing costs by eliminating scrap losses [1]. In the modern era, the inspection process also needs to be automatic, fast and accurate [2]. “Machine vision is the technology and methods used to provide imaging-based automatic inspection and analysis [3].” However, highly specular (mirror-like) surfaces are still proven to be the limitation of many state-of-art three-dimensional (3D) reconstruction approaches. The specularity of the outer surface makes it difficult to 3D reconstruct the product model accurately. Along with accurate measurements, it is also essential to detect defects such as dents, bumps, cracks and scratches present in a product. As these defects are palpable and are not visible by the camera, it is tough to detect them using vision-based inspection techniques in ambient lighting conditions. This paper presents an automated defect detection technique using the concepts of laser line projection and stereo vision. This research activity came up as an evolution of a previous study in which, the ideas of stereo-vision reconstruction and laser line projection were used, for accurate 3D measurement of highly specular surfaces. In this paper, the detection of three defect types (Dents, Scratches and Bumps) are examined in ambient lighting conditions. In the end, the output 3D profile of the defected product is compared with the non-defective product for accuracy evaluation.