Dynamic phase-differencing profilometry with number-theoretical phase unwrapping and interleaved projection.

High-speed 3D measurement is receiving increasing attention. However, simultaneously achieving high computational efficiency, algorithmic robustness, and reconstructing ratio is challenging. Therefore, a dynamic phase-differencing profilometry (DPDP) is proposed. By capturing the minimum three phase-shifting sinusoidal deformed patterns and establishing a brand-new model, the phase difference between the object on the reference plane and the reference plane is directly resolved to effectively improve computational efficiency. Although it is wrapped, by using only two auxiliary complementary gratings with a purposely designed lower frequency, a DPDP-based number-theoretical temporal phase unwrapping (NT-TPU) algorithm is also proposed to unwrap the wrapped phase difference rather than the phase itself with high robustness. Furthermore, compared to existing PSP-based NT-TPU, the proposed NT-TPU can normally work under more relaxed restrictions. In order to accomplish a high reconstructing ratio, a pentabasic interleaved projection (PIP) strategy based on time division multiplexing is proposed. It can improve the reconstructing ratio from one reconstruction per every five patterns to an equivalent of one reconstruction per every 1.67 patterns. Experimental results demonstrate that the proposed method achieves high computational efficiency, high algorithmic robustness, and high reconstructing ratio simultaneously and has prospective application in high-speed 3D measurement.

Improved computer-generated moiré profilometry with flat image calibration.

An improved computer-generated moiré profilometry (CGMP) with flat image calibration is proposed. In CGMP, the purification of the AC component plays a decisive role. While a composite grating modulated with both the sinusoidal grating and its background light substitutes for the sinusoidal grating itself, the sinusoidal deformed pattern and flat image can be demodulated from the captured pattern. It is found that the sinusoidal deformed pattern and flat image may deviate, which is caused by ambient light. So flat image calibration is conducted to obtain a purer AC component that can effectively suppress the influence of ambient light and ensure the measurement accuracy, even if spectrum aliasing exists. Experimental results show the feasibility and validity of the proposed method.

Computer-generated Moiré profilometry.

A new 3D measuring method based on computer-generated moiré fringes is proposed. The two AC components of the 0-degree and 90-degree phase-shifted fringe patterns on reference plane are prepared in advance. While the AC component of the single-shot deformed pattern is multiplied by the two prepared AC components, respectively, two computer-generated moiré fringes can be retrieved. The ratio of the two computer-generated moiré fringes is just the tangent of the phase modulated by the object. It is of great potential in real-time or even dynamical 3D measurement due to its single-shot deformed pattern feature, and it avoids the influences of the object's reflectivity simultaneously. Compared to the Fourier transform profilometry, its error is smaller due to its higher first-order spectrum. Experimental results show the feasibility and validity of the proposed method.

Enhancing rural B&B management through machine learning and evolutionary game: A case study of rural revitalization in Yunnan, China.

The rural B&B industry is a key component of rural tourism, local economic development, and the wider rural revitalization strategy. Despite the abundance of tourism resources in Yunnan, the B&B sector faces significant challenges. It is therefore imperative to accurately identify the most pressing issues within the current B&B industry and formulate appropriate solutions to advance Yunnan's rural revitalization efforts. This study uses recent reviews of rural B&Bs on Ctrip.com and employs machine learning techniques, including Bert, CNN, LSTM, and GRU, to identify the key management challenges currently facing Yunnan's rural B&B industry. An analysis is then conducted to identify the key stakeholders involved in the process of improving the management of Yunnan's B&Bs. To assess the willingness of each stakeholder to support the improvement of the rural B&B industry, this paper establishes a three-party evolutionary game model and examines the dynamic evolutionary process of management improvement within Yunnan's rural B&B industry. Two scenarios of evolutionarily stable strategies are analyzed, and parameters impacting stakeholders' strategy choices are simulated and evaluated. The results show that: i) Improving the "human factor" is the top priority for the current management improvement because tourists are most concerned about the emotional experience. Operators need to focus on improving service attitude and emotional experience; ii) The main stakeholders in the current management optimization process of Yunnan B&Bs are the local government, B&B operators, and tourists. Under appropriate conditions, the evolutionarily stable strategy of (1, 1, 1) is reachable. iii) variables such as additional costs, tourists' choice preferences, and government penalties significantly affect the strategy choices of stakeholders, especially B&B operators. This paper offers effective strategies for improving B&B management that can benefit the government, B&B operators, and tourists, and ultimately contribute to the promotion of quality rural revitalization. The paper not only identifies focal areas for improving B&B management in rural Yunnan, but also provides an in-depth understanding of stakeholder dynamics. As a result, it provides valuable insights to further the cause of quality rural revitalization.

A tripartite game analysis of industrial structure upgrading and green development of regional economy: A case study of Shanxi Province, China.

In the contemporary context, both the upgrading of the industrial structure and the implementation of environmentally sustainable practices within the regional economy have emerged as central avenues for achieving quality development. This study examines the strategic behavior of local governments, capital, and people through the construction of a tripartite evolutionary game model. Subsequently, six different evolutionary stable strategy (ESS) are subjected to a comprehensive analysis. Finally, the parameters influencing the strategic decisions of each party are meticulously examined through simulation. The results of this study can be summarized as follows: First, it is shown that under appropriate conditions, all three entities support the scenario of stable development prospects associated with industrial structure upgrading (1, 1, 1). Second, the strategic choices made by capital and people depend on several factors, including existing profits, future benefits, and the costs associated with transformation. At the same time, local governments show a propensity to adopt incentive strategies. Ultimately, the research underscores the pronounced impact of future benefits, transformation costs, and the probability of success in industrial upgrading on all stakeholders, shaping their evolutionary trajectories and results. In particular, the probability of successful industrial structure upgrading exerts the greatest influence on evolutionary trajectories, while the possibility of government imposing carbon taxes and initial willingness primarily determine the evolutionary trajectory. This paper attempts to provide a new perspective on industrial structure upgrading and green development of the regional economy by combining evolutionary game theory and scenario analysis methods to promote the process of industrial structure upgrading and sustainable development.

Color-encoded single-shot computer-generated Moiré profilometry.

A color-encoded single-shot computer-generated Moiré profilometry (CSCGMP) is proposed. Two sinusoidal gratings with a π phase difference are encoded in red and blue channels respectively to combine a composite color grating. While this composite color grating is projected onto the measured object, the corresponding color deformed pattern can be captured. So two deformed patterns with a π phase difference are separated from its red and blue components respectively. After normalization and subtraction, the AC component of both separated deformed patterns can be extracted. If this AC component respectively multiplied by the two AC components of fringe patterns of reference plane with a π/2 phase difference prepared and saved on the computer in advance, two computer-generated Moiré fringes just respectively standing for sine and cosine of phase which is modulated by the height of the object relative to the reference plane are figured out. So the 3D shape of the measured object can be reconstructed with normal computer-generated Moiré profilometry. Both simulation and experimental results show the feasibility and validity of the proposed method. It has potential in real-time 3D measurement due to its single-shot feature.

A super-grayscale and real-time computer-generated Moiré profilometry using video grating projection.

By using the time-division multiplexing characteristics of the projector and the integral exposure characteristics of the charge coupled device (CCD) camera, a super-grayscale and real-time computer-generated Moiré profilometry based on video grating projection is proposed. The traditional digital static grating is of 256-grayscale at most. If an expected super-grayscale grating with a maximum grayscale of 766 is designed and divided into three 256-grayscale fringe patterns with balanced grayscale as far as possible, they can be synthesized into a repeated playing video grating instead of the traditional static grating. When the video grating is projected onto the measured object, as long as the exposure time is set to three times the refresh cycle of the video grating, the super-grayscale deformed patterns in the 766-grayscale can be captured with a 10-bit CCD camera, so that the deformed patterns are realistic. The digital error in computer-generated Moiré profilometry is effectively reduced. In addition, this method can expand the linear range of the deformed pattern by 20% in computer Moiré profilometry. Therefore, the proposed method has the perspectives of high accuracy and real-time measurement. Theoretical analysis and experimental results demonstrate the validity and capability of the proposed method.

Computer-generated moiré profilometry based on fringe-superposition.

A computer-generated moiré profilometry based on algebraic addition instead of algebraic multiplication is proposed. Firstly, the two AC components of the captured fringe patterns on the reference plane with [Formula: see text] phase difference are retrieved and saved in advance. While measuring, two sinusoidal gratings with [Formula: see text] phase difference are projected onto the measured object alternatively, and the corresponding deformed patterns are captured. Then the AC component of the captured deformed pattern can be separated exactly. When the positive and negative AC component of the captured deformed pattern are added to the two prestored AC components respectively, two moiré fringes only reflect sine and cosine of the object's phase information can be successfully generated via a series of data processing procedures. Finally, the phase distribution of the measured object can be extracted by arctangent of the ratio of these two moiré fringes. Compared with computer-generated moiré profilometry based on algebraic multiplication, this proposed method can reduce the effect of high frequency noise and residual DC component on measurement and improve the measurement accuracy. While compared with [Formula: see text] phase shifting FTP, this method can measure more complex objects with better measurement capability. Experimental results verify the feasibility and validity of the proposed method.

High precision computer-generated moiré profilometry.

Recently, a computer-generated moiré profilometry was proposed by our research group. It can effectively avoid the influence of the transient caused by moiré fringes' direct acquisition and generally owns a higher accuracy. But when the spatial spectrum of the captured deformed pattern is severely aliased caused by the measured object, the accuracy of this method may be affected to some extent due to the impure background light component extraction. So, a high precision computer-generated moiré profilometry based on background light component's accurate elimination is proposed. By adding an additional special phase-shifting sinusoidal grating to accurately extract valid information in the spatial domain and improve the sinusoidal feature of the pattern, the measurement precision can be improved effectively. Though the single-shot feature is broken, the real-time measuring feature is still maintained successfully. Experimental results show the feasibility and validity of the proposed method.