To measure the shape of object with high-speed and avoid the disturbance of the vibration is remaining challenges faced by structured-light projection method. This paper proposes a high-speed optical metrology by coding three cosine patterns into three channels of RGB model to form the pattern. When the color image is obtained by camera, it will be transformed to HSI color model (hue, saturation and intensity). The hue component is regarded as the phase information to retrieve the 3D shape of object with single image, while the saturation and intensity are applied to avoiding phase errors caused by height steps or spatially isolated surfaces. This method can be used to measure object with non-monochromatic surfaces after the color compensated. Experimental results verify the feasibility of the developed method.
Single line scanning is the main method in traditional 3D hand-held laser scanning, however its reconstruction speed is very slow and cumulative error is very large. Therefore, we propose a method to reconstruct the 3D profile by parallel multi-line 3D hand-held laser scanning. Firstly, we process the two images that contain multi-line laser stripes shot by the binocular cameras, and then the laser stripe centers will be extracted accurately. Then we use the approach of stereo vision principle, polar constraint and laser plane constraint to match the laser stripes of the left image and the right image correctly and reconstruct them quickly. Our experimental results prove the feasibility of this method, which improves the scanning speed and increases the scanning area greatly.
This paper presents an approach to extract accurate color edge information using encoded patterns in hue, saturation, and intensity (HSI) color space. This method is applied to one-shot shape acquisition. Theoretical analysis shows that the hue transition between primary and secondary colors in a color edge is based on light interference and diffraction. We set up a color transition model to illustrate the hue transition on an edge and then define the segmenting position of two stripes. By setting up an adaptive HSI color space, the colors of the stripes and subpixel edges are obtained precisely without a dark laboratory environment, in a low-cost processing algorithm. Since this method does not have any constraints for colors of neighboring stripes, the encoding is an easy procedure. The experimental results show that the edges of dense modulation patterns can be obtained under a complicated environment illumination, and the precision can ensure that the three-dimensional shape of the object is obtained reliably with only one image.