AUTHOR=Han Yibo , Li Xia , Li XiaoCui , Zhou Zhangbing , Li Jinshuo 

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

JOURNAL=Frontiers in Bioengineering and Biotechnology

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2022.865130

DOI=10.3389/fbioe.2022.865130

ISSN=2296-4185

ABSTRACT=Abstract: In this paper, a multidisciplinary cross-fusion of bionics, robotics, computer vision, and cloud service networks is 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 is analyzed, and improvement directions are proposed. The surface microlens array arrangement is designed, and the spaced surface bionic compound eye design principle cloud service network model is established for the adopted spaced-type circumferential hierarchical microlens array arrangement. To realize the target localization of the compound eye system, the content of each step of the localization scheme is discussed in detail. The distribution of virtual spherical targets is designed by using the subdivision of the positive icosahedron to ensure the uniformity of the targets. The spot image is pre-processed to achieve spot segmentation. The energy symmetry-based spot center localization algorithm is explored and its localization effect is verified. Study the spot evaluation index, design the spot data screening algorithm, and complete the matching of the spot and sub-eye channels by the pattern of spot arrangement in the image and the angle information when acquiring the image. Select a suitable spatial interpolation method 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 is built and images are acquired. A super-resolution reconstruction algorithm combining pixel rearrangement and an improved iterative inverse projection method is used for image processing. The model is trained and evaluated in terms of detection accuracy, leakage rate, time overhead, and other evaluation indexes, and the test results show 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 comparison algorithm, the correct rate of the algorithm is increased by 21.72%. Through the research of this paper, the wide-field bionic compound eye target recognition and detection and cloud service network are organically combined to provide more technical support for the design of wide-field bionic compound eye target recognition and detection system.