Normal-Based Flower Pollination Algorithm (FPA) for Solving 3D Point Set Registration via Rotation Optimization

Abstract

Compared with the registration methods based on local optimizations, the heuristic registration methods are less sensitive to the initial position, and a reasonable bound range is essential to ensure the registration validity. In practice, compared with a rotation bound range, which is periodic, the setting of the translation range is more difficult and manual interventions required, especially when the initial position is complex. Moreover, it has yet to be discussed in past research. Therefore, a normal-based registration method based on the flower pollination algorithm is proposed in this paper, in which only rotation parameters (r x ,r y ,r z) are considered. In our method, the point correspondences are guided by their normal due to their invariance to position translation. Considering the normal degeneration caused by noise, outliers, and partial overlapping, the Pauta criterion is employed to remove distorted correspondences and acquire reliable translation. Moreover, the population of optimal pollens is guaranteed by the use of the searching radius adjustment and periodic boundary. A number of experiments demonstrate that the proposed method exhibits competitive or better performance in terms of initial position, noise, outliers and partial overlapping. Furthermore, a real quality inspection is also implemented to confirm the availability and superiority of the proposed method in the manufacturing process. INDEX TERMS Iterative closest points (ICP), heuristic registration method, flower pollination algorithm, Pauta criterion, quality inspection.

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“…Shen et al, 2020: In [ 53 ], the authors propose an algorithm derived from the Flower Pollination Algorithm (FPA) [ 54 ] to register 3D cloud points. Traditional registration of 3D cloud points involves both translation and rotation on all three axes.…”

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“…Flower grading based on machine vision has been studied by many researchers. Most of the publications are based on two-dimensional (2D) digital images and mainly focus on the defects, colors, and shapes of flowers [11][12][13][14][15][16][17]. However, limited by its own dimensionality, it is difficult to obtain a flower's real morphology from a 2D image.…”