4.7 Article

Recognition and Detection of Wide Field Bionic Compound Eye Target Based on Cloud Service Network

Journal

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fbioe.2022.865130

Keywords

cloud service network; wide-field bionic compound eye; image localization; target recognition detection; energy symmetry

Funding

  1. Henan Science and Technology Plan Project [212102210378]
  2. Research on Key Technologies of Intelligent Adaptation and Collaborative Optimization of IoT Services for Edge Computing [201913502]
  3. Research on Intelligent Mining and Recommendation of Zhang Zhongjing Prescription Based on Deep Neural Network

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This paper uses a multidisciplinary cross-fusion research platform to study wide-field bionic compound eye target recognition and detection from multiple perspectives. The research status is analyzed and improvement directions are proposed. Design principles and experimental platforms are established, and image processing algorithms are used for target localization and detection. The cloud service network-based wide-field bionic compound eye target recognition and detection system performs well in terms of detection accuracy and leakage rate.
In this paper, a multidisciplinary cross-fusion of bionics, robotics, computer vision, and cloud service networks was used as a research platform to study wide-field bionic compound eye target recognition and detection from multiple perspectives. The current research status of wide-field bionic compound-eye target recognition and detection was analyzed, and improvement directions were proposed. The surface microlens array arrangement was designed, and the spaced surface bionic compound eye design principle cloud service network model was established for the adopted spaced-type circumferential hierarchical microlens array arrangement. In order to realize the target localization of the compound eye system, the content of each step of the localization scheme was discussed in detail. The distribution of virtual spherical targets was designed by using the subdivision of the positive icosahedron to ensure the uniformity of the targets. The spot image was pre-processed to achieve spot segmentation. The energy symmetry-based spot center localization algorithm was explored and its localization effect was verified. A suitable spatial interpolation method was selected to establish the mapping relationship between target angle and spot coordinates. An experimental platform of wide-field bionic compound eye target recognition and detection system was acquired. A super-resolution reconstruction algorithm combining pixel rearrangement and an improved iterative inverse projection method was used for image processing. The model was trained and evaluated in terms of detection accuracy, leakage rate, time overhead, and other evaluation indexes, and the test results showed that the cloud service network-based wide-field bionic compound eye target recognition and detection performs well in terms of detection accuracy and leakage rate. Compared with the traditional algorithm, the correct rate of the algorithm was increased by 21.72%. Through the research of this paper, the wide-field bionic compound eye target recognition and detection and cloud service network were organically provide more technical support for the design of wide-field bionic compound eye target recognition and detection system.

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