scholarly journals Multiband Polarization Imaging

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Yongqiang Zhao ◽  
Qunnie Peng ◽  
Chen Yi ◽  
Seong G. Kong
Keyword(s):  
Vision System ◽  
Specular Reflection ◽  
Imaging Techniques ◽  
Polarized Light ◽  
Medical Diagnostics ◽  
Polarization Imaging ◽  
Low Contrast ◽  
Visual Sensing ◽  
Simultaneous Acquisition ◽  
Operating Environments

Multiband polarization imaging is an emerging sensing method that enables simultaneous acquisition of multiband spectral and multiangle polarization information of an object of interest in the scene. Spectral signatures of the light reflected from a target reveal the characteristics of the material composing the target while polarized light provides useful information on the surface features such as light scattering and specular reflection. In multiband spectral imaging, combined spectral and polarization information offers a comprehensive representation of an object utilizing complementary spectral and polarization information in visual sensing. Multiband polarization imaging has demonstrated a potential in the recognition of targets in challenging operating environments such as low-contrast and hazy conditions. This paper presents the concept and recent advances of multiband polarization imaging techniques, in particular, a bioinspired multiband polarization vision system. Applications of multiband polarization imaging in various fields include atmospheric observation, object detection and classification, medical diagnostics, surveillance, and 3D object reconstruction.

Differential polarization imaging of sickled cells

1988 ◽  
Vol 46 ◽  
pp. 62-63
Author(s):  
Marcos F. Maestre
Keyword(s):  
Optical Properties ◽  
Theoretical Approach ◽  
Polarized Light ◽  
Polarization Microscopy ◽  
Spectroscopic Techniques ◽  
Polarization Imaging ◽  
Circularly Polarized Light ◽  
Circularly Polarized ◽  
Microscopic Scale ◽  
Chiral Structures

Recently we have developed a form of polarization microscopy that forms images using optical properties that have previously been limited to macroscopic samples. This has given us a new window into the distribution of structure on a microscopic scale. We have coined the name differential polarization microscopy to identify the images obtained that are due to certain polarization dependent effects. Differential polarization microscopy has its origins in various spectroscopic techniques that have been used to study longer range structures in solution as well as solids. The differential scattering of circularly polarized light has been shown to be dependent on the long range chiral order, both theoretically and experimentally. The same theoretical approach was used to show that images due to differential scattering of circularly polarized light will give images dependent on chiral structures. With large helices (greater than the wavelength of light) the pitch and radius of the helix could be measured directly from these images.

scholarly journals Model of colposcopy using polarized light and effective early

2017 ◽  
Vol 20 (K2) ◽  
pp. 96-100
Author(s):  
Cat Ngoc Khuong Phan ◽  
Linh Quang Huynh ◽  
Quynh Ngoc Nguyen ◽  
Duong Cao Ly
Keyword(s):  
Imaging Techniques ◽  
Polarized Light ◽  
Analysis And Evaluation ◽  
Common Features ◽  
Common Diseases ◽  
Cervical Disease ◽  
Examination Methods ◽  
The Common ◽  
Image Processing Algorithms ◽  
Processing Algorithms

Cervical disease is one of the common diseases, it occurs in women and has a growing tendency. In particular, cervical cancer is one of the most common diseases. The disease can be cured if it is detected early and treated under the guidance of a physician. The usual cervical examination methods are biopsies, and colposcopy. Recently, many studies have applied imaging techniques in the analysis and evaluation of cervical pathology characteristics [1-3]. In this study, we improved the traditional colposcopy with a polarized light source, and captured images with high resolution. Based on the image obtained, we developed image processing algorithms, initially analyzed and evaluated some of the common features of cervical disease

Polarization analysis in the crayfish visual system

2001 ◽  
Vol 204 (14) ◽  
pp. 2383-2390 ◽  
Author(s):  
Raymon M. Glantz
Keyword(s):  
Visual System ◽  
Motor Neurons ◽  
Polarized Light ◽  
Cell Types ◽  
Afferent Input ◽  
Polarization Sensitivity ◽  
Polarization Analysis ◽  
Low Contrast ◽  
Motion Responses ◽  
Light Flashes

SUMMARY It is proposed that polarization sensitivity at the most peripheral stages of the crayfish visual system (lamina ganglionaris and medulla externa) is used to enhance contrast and thus may contribute to motion detection in low contrast environments. The four classes of visual interneurons that exhibit polarization sensitivity (lamina monopolar cells, tangential cells, sustaining fibers and dimming fibers) are not sensitive exclusively to polarized light but also respond to unpolarized contrast stimuli. Furthermore, many of these cells and the sustaining fibers in particular exhibit a greater differential e-vector responsiveness to a changing e-vector than to e-vector variations among steady-state stimuli. While all four cell types respond modestly to light flashes at an e-vector of 90° to the preferred orientation, the dynamic response to a changing e-vector is small or absent at this orientation. Because the sustaining fibers exhibit polarization sensitivity, and they provide afferent input to a subset of optomotor neurons, the latter were also tested for polarization sensitivity. The optomotor neurons involved in compensatory reflexes for body pitch were differentially sensitive to the e-vector angle of a flash of light, with maximum responses for e-vectors near the vertical. The motor neurons also exhibited a maximum response near the vertical e-vector to a continuously rotating polarizer. Two scenarios are described in which the sensitivity to a changing e-vector can produce motion responses in the absence of intensity contrast.

Applications of Dispersion Staining Technique in Image Analysis of Colorless Particles

2001 ◽  
Vol 7 (S2) ◽  
pp. 836-837
Author(s):  
Shu-Chun Su
Keyword(s):  
Image Analysis ◽  
Focal Plane ◽  
Imaging Techniques ◽  
Polarized Light ◽  
Staining Technique ◽  
Visible Range ◽  
Objective Lens ◽  
Conventional Imaging ◽  
Immersion Liquid ◽  
Staining Techniques

particles and their surrounding immersion liquid medium into a color in the When analyzing particle size distribution of colorless, translucent or transparent particles by image analysis, a major challenge is to obtain images of particles that ensure proper object detection, especially if the particles are amorphous or non-crystalline. Conventional imaging techniques, such as brightfield, darkfield, cross-polarized light, etc., might not applicable for these types of materials.Dispersion staining (DS) is a technique that coverts the refractive index (RI) difference between visible range and renders particles optically stained with that particular color. There are two modes of dispersion staining techniques: central stop (CS) and annular Stop (AS). For image analysis, CS is preferred.In the CS mode, the matching wavelength λm, i.e., the wavelength at which the RI of a particle equals that of liquid, is not refracted at the particle/liquid interface and therefore blocked by a 3-4 mm opaque round disk located at the center of the back focal plane of objective lens.

Responsive polymers for medical diagnostics

2020 ◽  
Vol 8 (29) ◽  
pp. 6217-6232
Author(s):  
Divambal Appavoo ◽  
Sung Young Park ◽  
Lei Zhai
Keyword(s):  
Molecular Recognition ◽  
Imaging Techniques ◽  
Medical Diagnostics ◽  
Diagnostic Assays ◽  
Responsive Polymers ◽  
Stimulus Responsive

Stimulus-responsive polymers have been used in improving the efficacy of medical diagnostics through different approaches including enhancing the contrast in imaging techniques and promoting the molecular recognition in diagnostic assays.

scholarly journals Oil seal surface defect detection using superpixel segmentation and circumferential difference

2020 ◽  
Vol 17 (6) ◽  
pp. 172988142097651
Author(s):  
Zhendong He ◽  
Jie Liu ◽  
Liying Jiang ◽  
Suna Zhao ◽  
Lei Zhang ◽  
...  
Keyword(s):  
Surface Defect ◽  
Surface Defects ◽  
Vision System ◽  
Small Variation ◽  
Low Contrast ◽  
Superpixel Segmentation ◽  
Surface Image ◽  
Surface Defect Detection ◽  
Key Issues ◽  
Background Difference

Surface defects affect the quality and safety of oil seals. It is a challenge to detect such defects in a vision system because of the unequal reflection property of oil seal surfaces and low contrast between the defect and the background. This article proposes a visual detection method (VDM) for oil seal surface defects and outlines two key issues of VDMs. First, we present a superpixel segmentation algorithm based on the significant gray level variation in the radial direction of an oil seal surface image. This image is then divided into several ring belts. Subsequently, considering the reflection inequality and low contrast, we propose a new circumferential background difference algorithm based on the small variation along the circumferential direction of the image. This algorithm eliminates the influence of the reflection inequality and improves the contrast distinction between the defects and the background. The experimental results verify the effectiveness of the proposed method with a recall and precision as high as 95.2% and 86.8%, respectively.

Overview of industrial machine vision

1984 ◽  
Vol 42 ◽  
pp. 550-553
Author(s):  
Jon R. Mandeville
Keyword(s):  
Machine Vision ◽  
Cognitive Processing ◽  
Vision System ◽  
Human Vision ◽  
Artificial Vision ◽  
Visual Environment ◽  
Computational System ◽  
Visual Sensing ◽  
Significant Research ◽  
Industrial Machine

One hardly needs to emphasize the importance of visual sensing and interpretation in our everyday lives and the severe limitations and handicaps imposed on the blind. The importance of human vision has motivated an intense interest in and significant research on artificial vision systems over the last 20 years. The relatively new, fast growing discipline of “machine (or computer) vision” is an outgrowth of this research.Machine vision is computation on images to produce useful, meaningful descriptions of a visual environment. A machine vision system may be used either as a symbiotic enhancement to human vision or as the perceptual component of an autonomous, goal-driven computational system capable of cognitive processing.

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