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J. Imaging, Volume 4, Issue 4 (April 2018)

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Cover Story (view full-size image) This paper describes a system for acquiring high dynamic range (HDR), spectral, and omnidirectional [...] Read more.
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Open AccessReview Cerebral Hemodynamic Influences in Task-Related Functional Magnetic Resonance Imaging and Near-Infrared Spectroscopy in Acute Sport-Related Concussion: A Review
J. Imaging 2018, 4(4), 59; https://doi.org/10.3390/jimaging4040059
Received: 28 February 2018 / Revised: 28 March 2018 / Accepted: 13 April 2018 / Published: 17 April 2018
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Abstract
One of the challenges of managing athletes with sport-related concussion (SRC) is guiding them to a safe return to play. A potential biomarker for use in the clinical assessment of recovery is the analysis of brain activation patterns during task-related functional Magnetic Resonance
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One of the challenges of managing athletes with sport-related concussion (SRC) is guiding them to a safe return to play. A potential biomarker for use in the clinical assessment of recovery is the analysis of brain activation patterns during task-related functional Magnetic Resonance Imaging (fMRI). However, fMRI studies have provided conflicting results regarding what is pathological. An element that can contribute to this disagreement are hemodynamic impairments of the brain that follow a concussion. A functional neuroimaging technique based on the optical properties of brain tissue—called functional near-infrared spectroscopy (fNIRS)—can be used to evaluate SRC athletes, partially taking into consideration these brain hemodynamic impairments. However, so far, fNIRS has not been extensively used in concussion. In this critical review, there is a description of the main fMRI results involving the neocortex in acutely concussed patients, the influences of hemodynamic impairments on fMRI and fNIRS and the advantages and disadvantages of fNIRS to limit this influence. Full article
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Open AccessArticle Non-Destructive Testing of Archaeological Findings by Grating-Based X-Ray Phase-Contrast and Dark-Field Imaging
J. Imaging 2018, 4(4), 58; https://doi.org/10.3390/jimaging4040058
Received: 28 February 2018 / Revised: 28 March 2018 / Accepted: 10 April 2018 / Published: 14 April 2018
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Abstract
The analysis of archaeological findings reveals the remaining secrets of human history. However, it is a challenging task to investigate and simultaneously preserve the unique remains. Available non-destructive examination methods are limited and often insufficient. Thus, we considered X-ray grating interferometry as a
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The analysis of archaeological findings reveals the remaining secrets of human history. However, it is a challenging task to investigate and simultaneously preserve the unique remains. Available non-destructive examination methods are limited and often insufficient. Thus, we considered X-ray grating interferometry as a non-destructive and advanced X-ray imaging method to retrieve more information about archaeological findings. In addition to the conventional attenuation image, the differential phase and the dark-field image are obtained. We studied the potential of the scattering-sensitive dark-field and the phase-shift sensitive differential phase image to analyse archaeological findings. Hereby, the focus lies on organic remnants. Usually, the organic materials have vanished due to decomposition processes, but the structures are often preserved by mineralisation and penetration of corrosion products. We proved that the combination of the attenuation and the dark-field image in particular, enables a separation of structural properties for fabric remnants. Furthermore, we achieved promising results for the reconstruction of sub-pixel sized fibre orientations of woven fabric remnants by employing the directional dark-field imaging method. We conclude from our results that a further application of X-ray dark-field imaging on wet organic findings and on the distinction of different types of organic remnants at archaeological findings is promising. Full article
(This article belongs to the Special Issue Phase-Contrast and Dark-Field Imaging)
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Open AccessArticle Text/Non-Text Separation from Handwritten Document Images Using LBP Based Features: An Empirical Study
J. Imaging 2018, 4(4), 57; https://doi.org/10.3390/jimaging4040057
Received: 15 December 2017 / Revised: 29 March 2018 / Accepted: 6 April 2018 / Published: 12 April 2018
Cited by 2 | Viewed by 1993 | PDF Full-text (15101 KB) | HTML Full-text | XML Full-text
Abstract
Isolating non-text components from the text components present in handwritten document images is an important but less explored research area. Addressing this issue, in this paper, we have presented an empirical study on the applicability of various Local Binary Pattern (LBP) based texture
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Isolating non-text components from the text components present in handwritten document images is an important but less explored research area. Addressing this issue, in this paper, we have presented an empirical study on the applicability of various Local Binary Pattern (LBP) based texture features for this problem. This paper also proposes a minor modification in one of the variants of the LBP operator to achieve better performance in the text/non-text classification problem. The feature descriptors are then evaluated on a database, made up of images from 104 handwritten laboratory copies and class notes of various engineering and science branches, using five well-known classifiers. Classification results reflect the effectiveness of LBP-based feature descriptors in text/non-text separation. Full article
(This article belongs to the Special Issue Document Image Processing) Printed Edition available
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Open AccessFeature PaperArticle Detection of Orientation-Modulation Embedded Data in Color Printed Natural Images
J. Imaging 2018, 4(4), 56; https://doi.org/10.3390/jimaging4040056
Received: 10 March 2018 / Revised: 27 March 2018 / Accepted: 29 March 2018 / Published: 4 April 2018
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Abstract
This article addresses methods for detection of orientation-modulation data embedded in color dispersed-dot-halftone images. Several state-of-the-art methods for detection of orientation-embedded data in printed halftone images have been proposed, however they have only been evaluated independently without comparing with each other. We propose
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This article addresses methods for detection of orientation-modulation data embedded in color dispersed-dot-halftone images. Several state-of-the-art methods for detection of orientation-embedded data in printed halftone images have been proposed, however they have only been evaluated independently without comparing with each other. We propose an improved detection method, which is using Principal Component Analysis (PCA) components as oriented-feature extractors, and a probabilistic model for the print-and-scan channel for maximum likelihood detection. The proposed detector and four state-of-the-art detectors are compared with each other in terms of correct detection rate, using a comprehensive testing set of printed natural images captured with three different devices. The proposed detector achieves highest correct detection rate using fewer feature extractors than the other methods, and it is significantly more robust to non-calibrated devices used for capturing the printed images. This is mostly due to the improved PCA-based oriented-feature extractors that are responsive to the embedded orientations and robust and insensitive to the other visual content. Full article
(This article belongs to the Special Issue Computational Colour Imaging)
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Open AccessReview Neutron Imaging at Compact Accelerator-Driven Neutron Sources in Japan
J. Imaging 2018, 4(4), 55; https://doi.org/10.3390/jimaging4040055
Received: 8 November 2017 / Revised: 28 February 2018 / Accepted: 22 March 2018 / Published: 27 March 2018
Cited by 1 | Viewed by 2002 | PDF Full-text (6370 KB) | HTML Full-text | XML Full-text
Abstract
Neutron imaging has been recognized to be very useful to investigate inside of materials and products that cannot be seen by X-ray. New imaging methods using the pulsed structure of neutron sources based on accelerators has been developed also at compact accelerator-driven neutron
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Neutron imaging has been recognized to be very useful to investigate inside of materials and products that cannot be seen by X-ray. New imaging methods using the pulsed structure of neutron sources based on accelerators has been developed also at compact accelerator-driven neutron sources and opened new application fields in neutron imaging. The world’s first dedicated imaging instrument at pulsed neutron sources was constructed at J-PARC in Japan owing to the development of such new methods. Then, usefulness of the compact accelerator-driven neutron sources in neutron science was recognized and such facilities were newly constructed in Japan. Now, existing and new sources have been used for neutron imaging. Traditional imaging and newly developed pulsed neutron imaging such as Bragg edge transmission have been applied to various fields by using compact and large neutron facilities. Here, compact accelerator-driven neutron sources used for imaging in Japan are introduced and some of their activities are presented. Full article
(This article belongs to the Special Issue Neutron Imaging)
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Open AccessArticle Preventing Wine Counterfeiting by Individual Cork Stopper Recognition Using Image Processing Technologies
J. Imaging 2018, 4(4), 54; https://doi.org/10.3390/jimaging4040054
Received: 25 January 2018 / Revised: 2 March 2018 / Accepted: 20 March 2018 / Published: 23 March 2018
Cited by 2 | Viewed by 1897 | PDF Full-text (10645 KB) | HTML Full-text | XML Full-text
Abstract
Wine counterfeiting is a major problem worldwide. Within this context, an approach to the problem of discerning original wine bottles from forged ones is the use of natural features present in the product, object and/or material (using it “as is”). The proposed application
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Wine counterfeiting is a major problem worldwide. Within this context, an approach to the problem of discerning original wine bottles from forged ones is the use of natural features present in the product, object and/or material (using it “as is”). The proposed application uses the cork stopper as a unique fingerprint, combined with state of the art image processing techniques to achieve individual object recognition and smartphones as the authentication equipment. The anti-counterfeiting scheme is divided into two phases: an enrollment phase, where every bottle is registered in a database using a photo of its cork stopper inside the bottle; and a verification phase, where an end-user/retailer captures a photo of the cork stopper using a regular smartphone, compares the photo with the previously-stored one and retrieves it if the wine bottle was previously registered. To evaluate the performance of the proposed application, two datasets of natural/agglomerate cork stoppers were built, totaling 1000 photos. The worst case results show a 100% precision ratio, an accuracy of 99.94% and a recall of 94.00%, using different smartphones. The perfect score in precision is a promising result, proving that this system can be applied to the prevention of wine counterfeiting and consumer/retailer security when purchasing a wine bottle. Full article
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Open AccessArticle High-Dynamic-Range Spectral Imaging System for Omnidirectional Scene Capture
J. Imaging 2018, 4(4), 53; https://doi.org/10.3390/jimaging4040053
Received: 15 December 2017 / Revised: 20 February 2018 / Accepted: 21 March 2018 / Published: 23 March 2018
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Abstract
Omnidirectional imaging technology has been widely used for scene archiving. It has been a crucial technology in many fields including computer vision, image analysis and virtual reality. It should be noted that the dynamic range of luminance values in a natural scene is
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Omnidirectional imaging technology has been widely used for scene archiving. It has been a crucial technology in many fields including computer vision, image analysis and virtual reality. It should be noted that the dynamic range of luminance values in a natural scene is quite large, and the scenes containing various objects and light sources consist of various spectral power distributions. Therefore, this paper proposes a system for acquiring high dynamic range (HDR) spectral images for capturing omnidirectional scenes. The system is constructed using two programmable high-speed video cameras with specific lenses and a programmable rotating table. Two different types of color filters are mounted on the two-color video cameras for six-band image acquisition. We present several algorithms for HDR image synthesis, lens distortion correction, image registration, and omnidirectional image synthesis. Spectral power distributions of illuminants (color signals) are recovered from the captured six-band images based on the Wiener estimation algorithm. In this paper, we present two types of applications based on our imaging system: time-lapse imaging and gigapixel imaging. The performance of the proposed system is discussed in detail in terms of the system configurations, acquisition time, artifacts, and spectral estimation accuracy. Experimental results in actual scenes demonstrate that the proposed system is feasible and powerful for acquiring HDR spectral scenes through time-lapse or gigapixel omnidirectional imaging approaches. Finally, we apply the captured omnidirectional images to time-lapse spectral Computer Graphics (CG) renderings and spectral-based relighting of an indoor gigapixel image. Full article
(This article belongs to the Special Issue Theory and Practice of High-Dynamic Range Imaging)
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Open AccessReview Contribution of Remote Sensing on Crop Models: A Review
J. Imaging 2018, 4(4), 52; https://doi.org/10.3390/jimaging4040052
Received: 31 December 2017 / Revised: 16 March 2018 / Accepted: 20 March 2018 / Published: 23 March 2018
Cited by 2 | Viewed by 2028 | PDF Full-text (7410 KB) | HTML Full-text | XML Full-text
Abstract
Crop growth models simulate the relationship between plants and the environment to predict the expected yield for applications such as crop management and agronomic decision making, as well as to study the potential impacts of climate change on food security. A major limitation
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Crop growth models simulate the relationship between plants and the environment to predict the expected yield for applications such as crop management and agronomic decision making, as well as to study the potential impacts of climate change on food security. A major limitation of crop growth models is the lack of spatial information on the actual conditions of each field or region. Remote sensing can provide the missing spatial information required by crop models for improved yield prediction. This paper reviews the most recent information about remote sensing data and their contribution to crop growth models. It reviews the main types, applications, limitations and advantages of remote sensing data and crop models. It examines the main methods by which remote sensing data and crop growth models can be combined. As the spatial resolution of most remote sensing data varies from sub-meter to 1 km, the issue of selecting the appropriate scale is examined in conjunction with their temporal resolution. The expected future trends are discussed, considering the new and planned remote sensing platforms, emergent applications of crop models and their expected improvement to incorporate automatically the increasingly available remotely sensed products. Full article
(This article belongs to the Special Issue Remote and Proximal Sensing Applications in Agriculture)
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