A Real-Time Iris Image Acquisition Algorithm Based on Specular Reflection and Eye Model

Iris Image Acquisition and Real-Time Detection System Using Convolutional Neural Network

10.21203/rs.3.rs-453519/v1 ◽

2021 ◽

Author(s):

Yuan Hu ◽

Xiaoyong Si

Keyword(s):

Neural Network ◽

Data Acquisition ◽

Convolutional Neural Network ◽

Real Time ◽

Error Rate ◽

Detection System ◽

Image Acquisition ◽

Iris Image ◽

Bilateral Filters ◽

Iris Data

Abstract The aim is to further improve the efficiency of iris detection and ensure real-time iris data acquisition. Here, the light field refocusing algorithm can collect the data in real-time based on the existing iris data acquisition and detection system, and the DL (Deep Learning) CNN (Convolutional Neural Network) is introduced. Consequently, an iris image acquisition and real-time detection system based on CNN is proposed, and the system for image acquisition, processing, and displaying is constructed based on FPGA (Field Programmable Gate Array). The spatial filtering algorithm can compare the performance of the proposed bilateral filters with common filters. The results indicate that the proposed bilateral filters can pick out qualified iris images in real-time, greatly improving the accuracy of the iris image recognition system. The average time for real-time quality assessment of each frame image is less than 0.05 seconds. The classification accuracy of the iris image quality assessment algorithm based on DL is 96.38%, higher than the other two algorithms, and the average classification error rate is 3.69%, lower than the average error rate of other algorithms. The results can provide a reference for real-time iris image detection and data acquisition.

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Real-time Approximation of Photometric Polygonal Lights

Proceedings of the ACM on Computer Graphics and Interactive Techniques ◽

10.1145/3384537 ◽

2020 ◽

Vol 3 (1) ◽

pp. 1-18

Author(s):

Christian Luksch ◽

Lukas Prost ◽

Michael Wimmer

Keyword(s):

Real Time ◽

Specular Reflection ◽

Near Field ◽

Measurement Data ◽

Data Sets ◽

Photometric Measurement ◽

Integration Technique ◽

Time Approximation ◽

Light Emitter ◽

Selection Of

We present a real-time rendering technique for photometric polygonal lights. Our method uses a numerical integration technique based on a triangulation to calculate noise-free diffuse shading. We include a dynamic point in the triangulation that provides a continuous near-field illumination resembling the shape of the light emitter and its characteristics. We evaluate the accuracy of our approach with a diverse selection of photometric measurement data sets in a comprehensive benchmark framework. Furthermore, we provide an extension for specular reflection on surfaces with arbitrary roughness that facilitates the use of existing real-time shading techniques. Our technique is easy to integrate into real-time rendering systems and extends the range of possible applications with photometric area lights.

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Module to Support Real-Time Microscopic Imaging of Living Organisms on Ground-Based Microgravity Analogs

Applied Sciences ◽

10.3390/app11073122 ◽

2021 ◽

Vol 11 (7) ◽

pp. 3122

Author(s):

Srujana Neelam ◽

Audrey Lee ◽

Michael A. Lane ◽

Ceasar Udave ◽

Howard G. Levine ◽

...

Keyword(s):

Real Time ◽

High Speed ◽

Simulated Microgravity ◽

Image Acquisition ◽

Time Lapse ◽

Moving Frames ◽

Cell Functions ◽

Microgravity Simulation ◽

Division Cell ◽

Over Time

Since opportunities for spaceflight experiments are scarce, ground-based microgravity simulation devices (MSDs) offer accessible and economical alternatives for gravitational biology studies. Among the MSDs, the random positioning machine (RPM) provides simulated microgravity conditions on the ground by randomizing rotating biological samples in two axes to distribute the Earth’s gravity vector in all directions over time. Real-time microscopy and image acquisition during microgravity simulation are of particular interest to enable the study of how basic cell functions, such as division, migration, and proliferation, progress under altered gravity conditions. However, these capabilities have been difficult to implement due to the constantly moving frames of the RPM as well as mechanical noise. Therefore, we developed an image acquisition module that can be mounted on an RPM to capture live images over time while the specimen is in the simulated microgravity (SMG) environment. This module integrates a digital microscope with a magnification range of 20× to 700×, a high-speed data transmission adaptor for the wireless streaming of time-lapse images, and a backlight illuminator to view the sample under brightfield and darkfield modes. With this module, we successfully demonstrated the real-time imaging of human cells cultured on an RPM in brightfield, lasting up to 80 h, and also visualized them in green fluorescent channel. This module was successful in monitoring cell morphology and in quantifying the rate of cell division, cell migration, and wound healing in SMG. It can be easily modified to study the response of other biological specimens to SMG.

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