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Biomimetics
Special Issues
Advanced Biologically Inspired Vision and Its Application
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Advanced Biologically Inspired Vision and Its Application

A special issue of Biomimetics (ISSN 2313-7673). This special issue belongs to the section "Bioinspired Sensorics, Information Processing and Control".

Deadline for manuscript submissions: 15 April 2025 | Viewed by 4885

Special Issue Editor

Dr. Jie Cao

E-Mail Website
Guest Editor
School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
Interests: bio-inspired vision; lidar; ghost imaging
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue will highlight 2D/3D imaging technologies, emphasizing the enhancement of resolution, speed, and precision through bionic approaches.

Intelligent perception technologies that leverage the synergy of multiple sensory inputs to augment system robustness and accuracy are of particular interest. We welcome case studies that demonstrate the application of these technologies in intelligent manufacturing, autonomous driving, and medical image analysis, showcasing their practical utility and transformative potential.

Interdisciplinary research that fuses principles from biology, computer science, and engineering to advance vision systems is strongly encouraged. We are especially interested in submissions that not only report novel findings but also propose innovative solutions to existing challenges in the field.

Dr. Jie Cao
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomimetics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • bionically inspired vision
  • laser 3D imaging
  • intelligent perception
  • autonomous vehicles
  • intelligent manufacturing
  • medical image analysis
  • interdisciplinary research
  • resolution enhancement
  • bionic vision applications

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

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Research

22 pages, 3763 KiB  
Article
Artificial Visual System for Stereo-Orientation Recognition Based on Hubel-Wiesel Model
by Bin Li, Yuki Todo and Zheng Tang
Biomimetics 2025, 10(1), 38; https://doi.org/10.3390/biomimetics10010038 - 8 Jan 2025
Viewed by 633
Abstract
Stereo-orientation selectivity is a fundamental neural mechanism in the brain that plays a crucial role in perception. However, due to the recognition process of high-dimensional spatial information commonly occurring in high-order cortex, we still know little about the mechanisms underlying stereo-orientation selectivity and [...] Read more.
Stereo-orientation selectivity is a fundamental neural mechanism in the brain that plays a crucial role in perception. However, due to the recognition process of high-dimensional spatial information commonly occurring in high-order cortex, we still know little about the mechanisms underlying stereo-orientation selectivity and lack a modeling strategy. A classical explanation for the mechanism of two-dimensional orientation selectivity within the primary visual cortex is based on the Hubel-Wiesel model, a cascading neural connection structure. The local-to-global information aggregation thought within the Hubel-Wiesel model not only contributed to neurophysiology but also inspired the development of computer vision fields. In this paper, we provide a clear and efficient conceptual understanding of stereo-orientation selectivity and propose a quantitative explanation for its generation based on the thought of local-to-global information aggregation within the Hubel-Wiesel model and develop an artificial visual system (AVS) for stereo-orientation recognition. Our approach involves modeling depth selective cells to receive depth information, simple stereo-orientation selective cells for combining distinct depth information inputs to generate various local stereo-orientation selectivity, and complex stereo-orientation selective cells responsible for integrating the same local information to generate global stereo-orientation selectivity. Simulation results demonstrate that our AVS is effective in stereo-orientation recognition and robust against spatial noise jitters. AVS achieved an overall over 90% accuracy on noise data in orientation recognition tasks, significantly outperforming deep models. In addition, the AVS contributes to enhancing deep models’ performance, robustness, and stability in 3D object recognition tasks. Notably, AVS enhanced the TransNeXt model in improving its overall performance from 73.1% to 97.2% on the 3D-MNIST dataset and from 56.1% to 86.4% on the 3D-Fashion-MNIST dataset. Our explanation for the generation of stereo-orientation selectivity offers a reliable, explainable, and robust approach for extracting spatial features and provides a straightforward modeling method for neural computation research. Full article
(This article belongs to the Special Issue Advanced Biologically Inspired Vision and Its Application)
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25 pages, 5124 KiB  
Article
Visual System Inspired Algorithm for Enhanced Visibility in Coronary Angiograms (VIAEVCA)
by Hedva Spitzer, Yosef Shai Kashi, Morris Mosseri and Jacob Erel
Biomimetics 2025, 10(1), 18; https://doi.org/10.3390/biomimetics10010018 - 1 Jan 2025
Viewed by 633
Abstract
Numerous efforts have been invested in previous algorithms to expose and enhance blood vessel (BV) visibility derived from clinical coronary angiography (CAG) procedures, such as noise reduction, segmentation, and background subtraction. Yet, the visibility of the BVs and their luminal content, particularly the [...] Read more.
Numerous efforts have been invested in previous algorithms to expose and enhance blood vessel (BV) visibility derived from clinical coronary angiography (CAG) procedures, such as noise reduction, segmentation, and background subtraction. Yet, the visibility of the BVs and their luminal content, particularly the small ones, is still limited. We propose a novel visibility enhancement algorithm, whose main body is inspired by a line completion mechanism of the visual system, i.e., lateral interactions. It facilitates the enhancement of the BVs along with simultaneous noise reduction. In addition, we developed a specific algorithm component that allows better visibility of small BVs and the various CAG tools utilized during the procedure. It is accomplished by enhancing the BVs’ fine resolutions, located in the coarse resolutions at the BV zone. The visibility of the most significant clinical features during the CAG procedure was evaluated and qualitatively compared by the consensus of two cardiologists (MM and JE) to the algorithm’s results. These included the visibility of the whole frame, the coronary BVs as well as the small ones, the main obstructive lesions within the BVs, and the various angiography interventional tools utilized during the procedure. The algorithm succeeded in producing better visibility of all these features, even under low-contrast or low-radiation conditions. Despite its major advantages, the algorithm also caused the appearance of disturbing vertebral and bony artifacts, which could somewhat lower diagnostic accuracy. Yet, viewing the processed images from multiple angles and not just from a single one and evaluating the cine mode usually overcomes this drawback. Thus, our novel algorithm potentially leads to a better clinical diagnosis, improved procedural capabilities, and a successful outcome. Full article
(This article belongs to the Special Issue Advanced Biologically Inspired Vision and Its Application)
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13 pages, 5286 KiB  
Article
Eye-Inspired Single-Pixel Imaging with Lateral Inhibition and Variable Resolution for Special Unmanned Vehicle Applications in Tunnel Inspection
by Bin Han, Quanchao Zhao, Moudan Shi, Kexin Wang, Yunan Shen, Jie Cao and Qun Hao
Biomimetics 2024, 9(12), 768; https://doi.org/10.3390/biomimetics9120768 - 18 Dec 2024
Viewed by 673
Abstract
This study presents a cutting-edge imaging technique for special unmanned vehicles (UAVs) designed to enhance tunnel inspection capabilities. This technique integrates ghost imaging inspired by the human visual system with lateral inhibition and variable resolution to improve environmental perception in challenging conditions, such [...] Read more.
This study presents a cutting-edge imaging technique for special unmanned vehicles (UAVs) designed to enhance tunnel inspection capabilities. This technique integrates ghost imaging inspired by the human visual system with lateral inhibition and variable resolution to improve environmental perception in challenging conditions, such as poor lighting and dust. By emulating the high-resolution foveal vision of the human eye, this method significantly enhances the efficiency and quality of image reconstruction for fine targets within the region of interest (ROI). This method utilizes non-uniform speckle patterns coupled with lateral inhibition to augment optical nonlinearity, leading to superior image quality and contrast. Lateral inhibition effectively suppresses background noise, thereby improving the imaging efficiency and substantially increasing the signal-to-noise ratio (SNR) in noisy environments. Extensive indoor experiments and field tests in actual tunnel settings validated the performance of this method. Variable-resolution sampling reduced the number of samples required by 50%, enhancing the reconstruction efficiency without compromising image quality. Field tests demonstrated the system’s ability to successfully image fine targets, such as cables, under dim and dusty conditions, achieving SNRs from 13.5 dB at 10% sampling to 27.7 dB at full sampling. The results underscore the potential of this technique for enhancing environmental perception in special unmanned vehicles, especially in GPS-denied environments with poor lighting and dust. Full article
(This article belongs to the Special Issue Advanced Biologically Inspired Vision and Its Application)
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11 pages, 2455 KiB  
Article
Dual-Coated Antireflective Film for Flexible and Robust Multi-Environmental Optoelectronic Applications
by Hyuk Jae Jang, Jaemin Jeon, Joo Ho Yun, Iqbal Shudha Tasnim, Soyeon Han, Heeyoung Lee, Sungguk An, Seungbeom Kang, Dongyeon Kim and Young Min Song
Biomimetics 2024, 9(10), 644; https://doi.org/10.3390/biomimetics9100644 - 20 Oct 2024
Viewed by 889
Abstract
Artificial antireflective nanostructured surfaces, inspired by moth eyes, effectively reduce optical losses at interfaces, offering significant advantages in enhancing optical performance in various optoelectronic applications, including solar cells, light-emitting diodes, and cameras. However, their limited flexibility and low surface hardness constrain their broader [...] Read more.
Artificial antireflective nanostructured surfaces, inspired by moth eyes, effectively reduce optical losses at interfaces, offering significant advantages in enhancing optical performance in various optoelectronic applications, including solar cells, light-emitting diodes, and cameras. However, their limited flexibility and low surface hardness constrain their broader use. In this study, we introduce a universal antireflective film by integrating nanostructures on both sides of a thin polycarbonate film. One side was thinly coated with Al2O3 for its high hardness, enhancing surface durability while maintaining flexibility. The opposite side was coated with SiO2 to optimize antireflective properties, making the film suitable for diverse environments (i.e., air, water, and adhesives). This dual-coating strategy resulted in a mechanically robust and flexible antireflective film with superior optical properties in various conditions. We demonstrated the universal capabilities of our antireflective film via optical simulations and experiments with the fabricated film in different environments. Full article
(This article belongs to the Special Issue Advanced Biologically Inspired Vision and Its Application)
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