Digital fringe projection (DFP) measurement technology has been widely used in research and industry due to its characteristics of fast measurement speed and easy implementation. However, when measuring objects with large surface undulations, the depth of field limitations of the camera and projector will cause part of the object to be measured to be in a state of defocus, which will reduce the measurement accuracy. This paper presents a novel method to discriminate the portion of an image that is defocused due to depth-of-field limitations and to eliminate the error caused by defocus in the phase diagram. The proposed approach first discriminates the defocused pixels in the image based on the modulation information, and then recovers the defocused regions by the information fusion method. The information fusion fixes the erroneous phase information by fusing the valid phase of the neighboring focused region with the phase of the defocused region obtained through kernel density estimation by means of the Kalman filter algorithm. Simulation and experimental results show that this method can effectively eliminate the errors caused by the depth-of-field limitation in the phase map, and can feasibly extend the depth of field of the digital fringe projection system without projecting additional images.
With the development of three-dimensional (3D) shape measurement technology, fringe projection has become an effective and reliable measurement method for its great performance on the robustness against environmental disturbance and ease of operation. Traditional method of fringe projection measurement using one projector and one camera needs multiple fringe patterns to project to get absolute phases. However, it always demands fast measuring speed in the condition of online measurement. In this work, one more camera is introduced to establish a binocular structured light system to extend the field of view. In addition, to improve the measurement speed, a triangular wave is supplemented to the sinusoidal fringe to form a superposed fringe to assist phase unwrapping with only three images projected. In the phase unwrapping process, geometric constraints are used to find the corresponding points in the images captured by left and right cameras, and then the unique corresponding points are selected by the embedded triangular waves and the period order is determined. Several experiments are performed and the results shows that the proposed method takes only one third of the time compared with the conventional measurement and thus can realize a fast 3D measurement by structured light.
The traditional method of line laser stripes extraction is to binarize the image taken by cameras with a threshold value, but the size of laser lines in different color areas are obviously different because the line laser is absorbed by different colors of the parts to be measured to different degrees. For some regions with similar color to the laser, the traditional laser fringe recognition method cannot even identify the laser line, which results in the serious vacancy of the points cloud obtained by linear structured light scanning in some regions. An adaptive threshold method for laser fringe extraction is proposed in this paper. A modified HSV space is firstly proposed and the characteristics of the laser stripes on different colors of cardboard based on the modified HSV space is analyzed. Then a new image with high contrast through the quantized characteristics of the stripes is synthesized; Finally, the neighborhood filtering method is used to perform filtering and the Steger method is employed to extract the center of the laser stripe. Experimental results show that the method proposed in this paper can better segment the laser fringe from the background than the traditional algorithm, which lays a good foundation for the calculation of laser fringe center and hence to improve the measuring capability of laser structured light.
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