Abstract: The near-infrared (NIR) camera is extensively used in the optical tracking system for surgical navigation because it can effectively restrain the interference from environmental light in the imaging process. The accuracy of the optical tracking system is determined by camera calibration. However, the existing calibration methods are intended for visible-light cameras and are inapplicable to NIR cameras because the latter has no capacity to capture the calibration pattern. In the study a calibration pattern composed of near-infrared surface-mounted diodes is designed, and the corresponding intelligent algorithm based on geometric information that can be used to calibrate the NIR camera is…proposed. Using this method requires the implementation of automatic decision of angular points via triangular gridding. The experimental results show that our proposed method is accurate and effective in meeting the application requirements of surgical navigation.
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Abstract: This paper applies the error-eliminating theory to create a new method for fuzzy multiple attribute decision-making problems whose attribute values contain interval numbers, triangular fuzzy numbers, and trapezoidal fuzzy numbers. First, the concepts of error, loss, and extreme loss are discussed in the context of fuzzy multiple attribute decision-making problems combined with error-eliminating theory. Second, the error function is constructed, and the extreme loss value is calculated based on decision makers’ psychological threshold interval and error types. Third, the attribute loss value is calculated through error values and extreme loss values based on the decision makers’ psychological characteristics of loss…aversion. And then, the overall loss value of alternatives is obtained by the attribute loss value. Finally, the ranking and selection of alternatives are conducted based on the overall loss value. Using the practical example of the location of agricultural products’ logistics center, the rationality and scientificity of this study are illustrated by comparing the decision-making method proposed in this paper with three other methods.
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Abstract: Diagnosis of rice planthopper pests based on imaging technology is an efficient means to develop intelligent agriculture. Effective contour automation extraction is an important pretreatment technology at the early stage for identifying and classifying rice planthoppers. The traditional graph cut method-based active contour (GCBAC) requires human–computer interaction during segmentation. In addition, GCBAC is prone to shrinking bias phenomenon, thereby providing short-boundary segmentation results. This study proposed a novel approach to overcome these two problems. First, rice planthopper initial segmentation was completed through discrete cosine transform to weaken the interference of background, and this segmentation was used as the initial contour…of GCBAC to avoid artificial contour initialization. Then, dilation direction of contour line on both sides was changed to a one-way lateral dilation to avoid boundary shrinking bias. Results show that the proposed method can accurately locate pest region and clearly segment the contour of rice planthoppers.
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