In this paper, the statistical properties of speckle pattern are investigated from the point of view of computer texture analysis, and a measurement method of an object surface roughness and the object surface displacement is subsequently put forward. In the geometrical information extraction technique, the speckle pattern images are taken by a very simple configuration of setup consisting of a laser and a CCD camera. Surface roughness and displacement information is extracted based on the energy feature characterization of the grey level co-occurrence matrices of the speckle pattern images. Our experimental results show that surface roughness and displacement contained in surface speckle pattern images have a good relationship with their energy feature. By means of a set of standard surface specimens with different roughness, the relation curve is readily calibrated. Then the surface roughness of an object surface made by same material and manufactured by the same way as the standard specimens can be evaluated from a single speckle pattern image taken from the surface. Similarly, the surface displacement can also be obtained from a single speckle pattern image. The easily implemented method can be used in-process surface roughness and displacement measurement.

A hybrid vision system for online measurement of surface roughness is introduced. The hybrid vision system applies two cameras for capturing the laser speckle pattern and scattering images simultaneously. With the help of advanced image processing, several features of texture and shape are computed for the surface roughness characterization. On the basis of experimental tests, feature fusion to improve measurement range and linearization of the measurement is also discussed.

On-line roughness measurement of a surface with one-dimensional manufacturing marks is difficult to implement. For example, a contact stylus-type inspection method often does not perform very well or fails without any prior knowledge of the mark distribution on the surface. In this paper, we propose an on-line surface roughness measurement method based on laser light scattering, which is very effective for roughness measurement of one-dimensional manufacturing surfaces. The surface roughness is obtained from the spatial distribution of the scattered light intensity. The measurement setup has a very simple configuration, which consists of a CCD sensor, a collimated diode laser and an expander. The orientation of the spatial distribution of the scattered light intensity from the surface, which depends on the surface orientation, is detected by the CCD sensor, and then the mark direction can be readily determined from image processing. After that the root-mean-square (RMS) height of the surface roughness is extracted by means of image processing of the scattered light distribution in the direction parallel to the manufacturing mark, rather than in the direction perpendicular to the mark which is often followed by other measurement probes. The experimental tests show that the non-contact method has great potential for on-line surface roughness measurement.

This paper reviews the recent progress in surface measurement methods using active vision and light-scattering techniques. The active vision methods with different structured light patterns and the corresponding techniques are summarized. The surface roughness and defects inspection with light-scattering are discussed. After the review, an integrative method to measure surface waviness and form, roughness is proposed.

Each sensor in a multi-sensor visual measurement system has its own local coordinate system to which its measurements are referred. To use the measurement results, the data need to be transformed into a global coordination system. This indicates that all of the local sensor systems relative to the global coordinate system need to be calibrated by a global calibration method. In this paper, a method for calibrating the coordinate systems of a large-scale multi-sensor visual measurement system is introduced. The method utilizes a theodolite coordinate measurement system based on a theodolite pair to realize the global calibration. During the global calibration process, the theodolite coordinate measurement system measures the 3D coordinates of the feature points within each visual sensor relative to a global coordinate system. Then the global calibration can be implemented by means of direct and indirect transformation methods depending on the calibration targets. The calibration method has been successfully applied in practical applications.