Figure - available from: Applied Optics
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DIC-based stereo correspondence for a speckle image pair using IC-GN algorithm; left and right images have been rectified to be in line alignment. The image pair is captured with projection of speckle pattern onto a plaster portrait.
Source publication
Human body measurement is essential in modern rehabilitation medicine, which can be effectively combined with the technology of additive manufacturing. Digital image correlation based on laser speckle projection is a single-shot, accurate, and robust technique for human body measurement. In this paper, we present a handheld anthropometric measureme...
Citations
... Structured light measurement is a highprecision area array measurement technology; stripe structured light generally needs to project multiple coded patterns to obtain complete high-resolution data, during the process the object needs to keep still. Speckle structured light is based on the principle of binocular stereo vision, which projects speckle patterns with high randomness and high contrast on the surface of the object, and then realizes accurate stereo matching by digital speckle correlation [13,14]. Therefore, the speckle projection-based 3D scanning technology is a single-shot 3D measurement technology with high precision. ...
... During the calibration process, the target blocks at both ends should be in the respective fields of view of the two sensors. The two target blocks are composed of two kinds of circular markers with different diameters, marker identification method can refer to our previous work [13]. It should be noted that the only difference between the two target blocks is whether there is a large circular marker in the center, so the two target blocks can be automatically distinguished during calibration. ...
Human body scanning is an important means to build a digital 3D model of the human body, which is the basis for intelligent clothing production, human obesity analysis, and medical plastic surgery applications, etc. Comparing to commonly used optical scanning technologies such as laser scanning and fringe structured light, infrared laser speckle projection-based 3D scanning technology has the advantages of single-shot, simple control, and avoiding light stimulation to human eyes. In this paper, a multi-sensor collaborative digital human body scanning system based on near-infrared laser speckle projection is proposed, which occupies less than 2 m2 and has a scanning period of about 60 s. Additionally, the system calibration method and control scheme are proposed for the scanning system, and the serial-parallel computing strategy is developed based on the unified computing equipment architecture (CUDA), so as to realize the rapid calculation and automatic registration of local point cloud data. Finally, the effectiveness and time efficiency of the system are evaluated through anthropometric experiments.
... Shape reconstruction via the speckle correlation method is based on the principle of binocular stereo vision; high randomness and highcontrast speckle patterns are projected onto the surface of the object to be measured, and binocular stereo matching is realized using the digital speckle correlation method [1,2]. It has been revealed that the fundamental principles of the speckle correlation-based 3D shape measurement method and fringe structured light-based method are the same, as both are based on binocular stereo vision, or more rigorously, triangulation imaging. ...
Speckle correlation-based 3D shape measurement technology has an increasing number of applications in the fields of medical assistance, cultural relic protection, product manufacturing, and inspection. The foremost process of this method is the stereo matching of speckle image pairs using digital image correlation (DIC). It is challenging to improve the matching precision of DIC for complex shapes with large or abrupt curvature changes. Because the local curvature change and surface shape complexity of different objects vary, first-order and second-order shape functions have different abilities to describe the mapping relationship from the reference subset to the target subset. As a result, the systematic errors caused by subset under-matching and over-matching are also different. In this study, a pixel-by-pixel dynamic shape function selection algorithm is proposed for different measurement objects or different regions on the surface of the same object. Experimental results show that the proposed algorithm can effectively suppress the measurement error caused by the limited description ability of a specific shape function.
