ScholarWorks@성균관대학교

초록

The global feature invariant moment plays a crucial role in capturing the feature information of a target. At present, the extraction of the target moment depends on the processing of the two-dimensional image, which leads to the high computational resource occupation due to the large amount of inherent data and the high information redundancy of the image. This reduces the real-time performance of target moment extraction to a certain extent. In order to solve this problem, we introduce a novel strategy for extracting Hu invariant moments, which is based on the combination of single-pixel detection technology and the Hu invariant moments theory. To the best of our knowledge, this is the first proposal of an image-free extraction strategy employing single-pixel detection. The extraction of moments is seamlessly integrated into the single-pixel detection process, facilitating efficient and rapid acquisition, followed by the construction of Hu invariant moments. Theoretical analysis and experimental validation of our proposed method are carried out, demonstrating the effective acquisition of Hu invariant moments. This technology holds substantial application value and prospects in various fields, including target analysis, understanding, classification, and recognition. © 2024 Elsevier Ltd

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