Xiaodong Tian

3D reconstruction and pose determination of the cutting tool from a single view

This paper addresses the problem of 3D reconstruction and orientation of the cutting tool on a machine tool after it is loaded onto the spindle. Considering the reconstruction efficiency and that a cutting tool is a typical object of surface of revolution (SOR), a method based on a single calibrated view is presented, which only involves simple perspective projection relationship. First, the position and the orientation of the cutting tool is determined from an image. Then the silhouette of the cutting tool on the image is used to generate the 3D model, section by section. The designed algorithm is presented. This method is applicable to various kinds of cutting tools. Simulation and actual experiments on a machine tool verify that the method is correct with an accuracy of less than 1 mm.

Automatic Segmentation of the Apparent Contour for 3D Modeling of Cutting Tools from Single View

One of the industrial applications for vision-based model reconstruction of surfaces of revolution (SOR) is to rebuild 3D models of rotating mill cutters. For this application, the automation of the process is crucial. One of the critical issues with the automation is the segmentation of the apparent contour. Therefore, this paper introduces a new approach for the automatic apparent contour extraction of SORs. It consists of three parts. Firstly, the region of SOR is located on image and the contour of SOR is extracted inside this region. Secondly, the extracted contour is partitioned into several portions based on curvature analysis. A property of SOR is used to verify the partitioning. Finally, the contour is classified into the apparent contours and the imaged cross sections by exploiting both 2D and 3D information. The experiment on machine tool verifies that the algorithms proposed are reliable and accurate in the industrial environment.

An Experimental Study of Reconstruction of Tool Cutting Edge Features Using Space Carving Method

The precedent of this project is to obtain a surface of revolution model of the machine tool cutter by using a single CCD camera on-machine. This paper introduces the possibility of locating the cutting edges of the cutter with reconstructed 3D models by using the same setup. Space carving method is proven useful for 3D model reconstruction of objects on a turn table. The spindle rotation of the cutter can simulate this effect. Using a calibrated camera and a known spindle speed, the images of a cutter are captured. The edge features of the cutter observed can be used for model reconstruction. Using this model of the cutter, the approximate location of the cutting edge can be located. The initial investigation shows that the accurate motion of the spindle is very important to obtain accurate results.

Line Extraction with Composite Background Subtract

This paper presents a line extraction method to process images taken inside a machine tool. Instead of using real background images, our approach utilizes a virtual background image. This approach solves the problem of absence of real background images due to a dynamic background. In order to only extract lines of the object, all corners are detected from the real image first. Then, those corners generated from the background are filtered through composite background subtraction. Afterwards, a hypothesis of a line exists between any two corners is made. All the hypothetical lines are mapped back to the original real image to test for their existence. Those lines caused by noises, such as reflections or scratches, can be then eliminated. Our experimental results prove the feasibility and effectiveness of this proposed method..

On-Machine Visual Modeling System With Object Recognition

This paper presents an on-machine modeling system that tries to bridge the gap between the design and the machining. This system is able to build a comprehensive solid model of the CNC machining workspace after the workpiece and fixtures have been installed onto the working table. This solid model can be used for simulation to enhance its credibility. For this purpose, one prototype of a 3D visual modeling system is proposed and designed. In order to accurately calibrate CCD cameras upon the absolute coordinate frame of the machining center, a practical calibration method is presented at first. To segment the target part and extract its 2D features on the captured images, the techniques of Image Decomposition and a modified Standard Hough Transform (SHT) are designed. Using these 2D features, the 3D visual stereovision system, powered by a designed feature matching engine, is capable of obtaining the 3D features of the target part. Furthermore, the part has been identified by the object recognition technology. This recognition includes part recognition and pose recognition. In the part recognition, the part is recognized and an initial pose transform is obtained. Using this initial pose transform, the pose optimization method, named as Dual Iterative Closest Lines (DICL), is designed to locate the optimum position and orientation of the solid model of the recognized part. Finally, this modeling system is tested on a machining center. The experimental result indicates the innovation and feasibility of the proposed modeling system.© 2005 ASME