Crossed-grating phase-shifting profilometry (CGPSP) has great utility in three-dimensional shape measurement due to its ability to acquire horizontal and vertical phase maps in a single measurement. However, CGPSP is extremely sensitive to the non-linearity effect of a digital fringe projection system, which is not studied in depth yet. In this paper, a mathematical model is established to analyze the phase error caused by the non-linearity effect. Subsequently, two methods used to eliminate the non-linearity error are discussed in detail. To be specific, a double five-step algorithm based on the mathematical model is proposed to passively suppress the second non-linearity. Furthermore, a precoding gamma correction method based on probability distribution function is introduced to actively attenuate the non-linearity of the captured crossed fringe. The comparison results show that the active gamma correction method requires less fringe patterns and can more effectively reduce the non-linearity error compared with the passive method. Finally, employing CGPSP with gamma correction, a faster and reliable inverse pattern projection is realized with less fringe patterns.

Shelling is a central and crucial step in the mechanized processing of scallops. However, current research on the peeling mechanism is insufficient, and a relatively complete theoretical system has not been established so far. This paper proposes an application of response surface methodology and the design of an experiment to provide and stimulate further research on the automation of scallop shucking. Effective factors on the binding force of scallops are evaluated and discussed in this paper. The relationship between responses with significant factors is established. By employing response surface methodology, mathematical regression model can be efficiently performed. This response model is applied to analyze the response surface contours and surface plots to estimate shelling performance by developing a better shucking process. At the same time, quadric model proposed is used not only for predicted optimal process parameters but also for process optimization, and enrich the theoretical system of shellfish shelling.

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