紧凑折反式仿生复眼及图像快速拼接识别算法

doi:10.12382/bgxb.2021.0393

兵工学报 ›› 2022, Vol. 43 ›› Issue (8): 1845-1857.doi: 10.12382/bgxb.2021.0393

紧凑折反式仿生复眼及图像快速拼接识别算法

曹昭睿¹，郝永平¹，刘万成²，白帆¹，孙颢洋¹，张慧³，李宇海²

(1.沈阳理工大学装备工程学院, 辽宁沈阳 110159; 2.光电信息控制和安全技术重点实验室, 天津 300308;3.沈阳理工大学机械工程学院, 辽宁沈阳 110159)

上线日期:2022-07-24
通讯作者: 郝永平(1960—),男,教授，博士生导师 E-mail:yphsit@126.com
作者简介:曹昭睿(1993—), 男, 博士研究生。E-mail: caozhaorui@163.com
基金资助:
国防科技基础加强计划技术领域基金项目(2020-JCJQ-JJ-422)；“十三五”装备预研兵器工业联合基金项目(6141B012841)；装备预研重点实验室基金项目(6142107190207)；辽宁省教育厅青年基金项目(LG201931)；国防科技重点实验室基金项目（2021JCJQLB055009）

Compact Catadioptric Bionic Compound Eye and Fast Image Mosaic Recognition Algorithm

CAO Zhaorui¹, HAO Yongping¹, LIU Wancheng², BAI Fan¹, SUN Haoyang¹, ZHANG Hui³, LI Yuhai²

(1. School of Equipment Engineering, Shenyang Ligong University, Shenyang 110159, Liaoning, China; 2. Science and Technology on Electro-optical Information Security Control Laboratory, 300308, Tianjin, China; 3. School of Mechanical Engineering, Shenyang Ligong University, Shenyang 110159, Liaoning, China)

Online:2022-07-24

摘要/Abstract

摘要： 针对多相机阵列复眼质量大与图像数据生成量高的问题，开展多通道-单探测器构型的大视场仿生复眼成像系统及其图像快速拼接识别算法的研究。通过光路折反与光程归一的方式，实现多视角子眼共像面与分区成像。根据折反式复眼成像特征，提出特征图级下基于区域结构相似性的图像快速拼接算法。配合目标识别卷积神经网络，实现紧凑空间下大视场全局图像的快速重建与目标识别。所提出的复眼系统有效光学视场角为138°×75°、光学尺寸为29.78 mm×19.74 mm× 6.86 mm、全局图像拼接速度为0.011 s。紧凑型折反式仿生复眼具有体积小、视场大、计算开销少的特点，能够为载荷与算力受限的小型无人设备与低速弹箭提供广域视觉成像与快速图像拼接识别能力。

关键词: 仿生复眼, 多孔径成像, 光路折反, 图像拼接, 目标识别

Abstract: To resolve the problems of high mass and high volume of image data generated by the multi-channel camera array in a bionic compound eye, a large FOV bionic compound eye imaging system and an image fast mosaic recognition algorithm based on multi-channel single detector is proposed. By using optical path refraction and normalization, multi view sub eye image plane coplanar and single photodetector partition imaging are realized. Based on the imaging characteristics of catadioptric eyes, an image mosaic algorithm based on the structural similarity at the feature map level is proposed. Fast reconstruction and target recognition of global images with a large field of view (FOV) in a compact space are realized by using a convolution neural network for target recognition. The proposed compound eye system has an effective optical FOV of 138°×75°, an optical dimension is 29.78 mm×19.74 mm×6.86 mm, and a global image mosaic speed is 0.011 s. The compact catadioptric compound eye has the advantages of small volume, large FOV, and low computational cost. It can provide wide area vision and fast image mosaic recognition capabilities for small unmanned equipment and low speed projectiles with limited load and computational power.

Key words: bioniccompoundeye, multi-apertureimaging, opticalpathcatadioptric, imagestitching, targetrecognition

中图分类号:

TH741

曹昭睿，郝永平，刘万成，白帆，孙颢洋，张慧，李宇海. 紧凑折反式仿生复眼及图像快速拼接识别算法[J]. 兵工学报, 2022, 43(8): 1845-1857.

CAO Zhaorui, HAO Yongping, LIU Wancheng, BAI Fan, SUN Haoyang, ZHANG Hui, LI Yuhai. Compact Catadioptric Bionic Compound Eye and Fast Image Mosaic Recognition Algorithm[J]. Acta Armamentarii, 2022, 43(8): 1845-1857.

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紧凑折反式仿生复眼及图像快速拼接识别算法

Compact Catadioptric Bionic Compound Eye and Fast Image Mosaic Recognition Algorithm

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