scholarly journals Three-Dimensional Reconstruction of Soybean Canopies Using Multisource Imaging for Phenotyping Analysis

2018 ◽  
Vol 10 (8) ◽  
pp. 1206 ◽  
Author(s):  
Haiou Guan ◽  
Meng Liu ◽  
Xiaodan Ma ◽  
Song Yu
Keyword(s):  
3D Reconstruction ◽  
Laser Scanning ◽  
Imaging System ◽  
Three Dimensional ◽  
Plant Phenotyping ◽  
Phenotypic Traits ◽  
Soybean Plant ◽  
Imaging Device ◽  
Soybean Canopy ◽  
Greenness Index

Geometric three-dimensional (3D) reconstruction has emerged as a powerful tool for plant phenotyping and plant breeding. Although laser scanning is one of the most intensely used sensing techniques for 3D reconstruction projects, it still has many limitations, such as the high investment cost. To overcome such limitations, in the present study, a low-cost, novel, and efficient imaging system consisting of a red-green-blue (RGB) camera and a photonic mixer detector (PMD) was developed, and its usability for plant phenotyping was demonstrated via a 3D reconstruction of a soybean plant that contains color information. To reconstruct soybean canopies, a density-based spatial clustering of applications with noise (DBSCAN) algorithm was used to extract canopy information from the raw 3D point cloud. Principal component analysis (PCA) and iterative closest point (ICP) algorithms were then used to register the multisource images for the 3D reconstruction of a soybean plant from both the side and top views. We then assessed phenotypic traits such as plant height and the greenness index based on the deviations of test samples. The results showed that compared with manual measurements, the side view-based assessments yielded a determination coefficient (R2) of 0.9890 for the estimation of soybean height and a R2 of 0.6059 for the estimation of soybean canopy greenness index; the top view-based assessment yielded a R2 of 0.9936 for the estimation of soybean height and a R2 of 0.8864 for the estimation of soybean canopy greenness. Together, the results indicated that an assembled 3D imaging device applying the algorithms developed in this study could be used as a reliable and robust platform for plant phenotyping, and potentially for automated and high-throughput applications under both natural light and indoor conditions.

scholarly journals POSSIBILITIES OF THE APPLICATION OF THREE-DIMENSIONAL TECHNOLOGIES AND MODERN TECHNOLOGICAL MEANS IN THE CRIME INVESTIGATION ACTIVITY

2018 ◽  
Vol 18 ◽  
pp. 98-105
Author(s):  
N. V. Pavliuk
Keyword(s):  
Digital Media ◽  
Technology Use ◽  
Laser Scanning ◽  
3D Model ◽  
Imaging System ◽  
3D Visualization ◽  
Three Dimensional ◽  
Scanning System ◽  
Crime Reconstruction ◽  
Technological Means

The issues related to the introduction of innovative methods, technologies and technological means in the investigation of crimes are considered. It is noted that one of the main directions of the development of Criminalistics is the assimilation of the virtual reality associated with computerization of spheres of life, implementation of modern technologies and their use in law enforcement. Technology use of laser scanning of terrain and objects resulting in 3D model is produced allows several times to increase informative value of data collected at the incident scene, provides a visual and convenient visualization in three-dimensional form. As against photo and video images, 3D model has a stereoscopic image and the ability to freely change the angle while viewing. Besides to scanning results can be stored on any digital media without the possibility of changes or adjustments. Attention is focused on the technological capabilities of 3D-visualization systems on examples of their use in foreign countries as technological means of capturing the situation of the scene and the subsequent of a crime reconstruction. Thus, using a portable three-dimensional imaging system for working with volumetric traces at a crime scene, it is possible to obtain accurate three-dimensional images of traces of protectors or footprints (shoes) on soil and snow. This system is an alternative to traditional methods of fixing evidence: photofixing and making plaster casts. Unlike other systems, new approach does not require the use of lasers. The expediency of expanding the range of 3D laser scanning system use in modern investigative and judicial practice of our state with the aim of increasing the level of provision of pre-trial investigation authorities with technological means and bringing it closer to European standards is argued.

scholarly journals Quantifying Variation in Soybean Due to Flood Using a Low-Cost 3D Imaging System

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2682 ◽  
Author(s):  
Wenyi Cao ◽  
Jing Zhou ◽  
Yanping Yuan ◽  
Heng Ye ◽  
Henry T. Nguyen ◽  
...  
Keyword(s):  
Plant Height ◽  
3D Imaging ◽  
Plant Architecture ◽  
Imaging System ◽  
Low Cost ◽  
Plant Phenotyping ◽  
Soybean Plant ◽  
Plant Canopy ◽  
Petiole Length ◽  
Dry Biomass

Flood has an important effect on plant growth by affecting their physiologic and biochemical properties. Soybean is one of the main cultivated crops in the world and the United States is one of the largest soybean producers. However, soybean plant is sensitive to flood stress that may cause slow growth, low yield, small crop production and result in significant economic loss. Therefore, it is critical to develop soybean cultivars that are tolerant to flood. One of the current bottlenecks in developing new crop cultivars is slow and inaccurate plant phenotyping that limits the genetic gain. This study aimed to develop a low-cost 3D imaging system to quantify the variation in the growth and biomass of soybean due to flood at its early growth stages. Two cultivars of soybeans, i.e. flood tolerant and flood sensitive, were planted in plant pots in a controlled greenhouse. A low-cost 3D imaging system was developed to take measurements of plant architecture including plant height, plant canopy width, petiole length, and petiole angle. It was found that the measurement error of the 3D imaging system was 5.8% in length and 5.0% in angle, which was sufficiently accurate and useful in plant phenotyping. Collected data were used to monitor the development of soybean after flood treatment. Dry biomass of soybean plant was measured at the end of the vegetative stage (two months after emergence). Results show that four groups had a significant difference in plant height, plant canopy width, petiole length, and petiole angle. Flood stress at early stages of soybean accelerated the growth of the flood-resistant plants in height and the petiole angle, however, restrained the development in plant canopy width and the petiole length of flood-sensitive plants. The dry biomass of flood-sensitive plants was near two to three times lower than that of resistant plants at the end of the vegetative stage. The results indicate that the developed low-cost 3D imaging system has the potential for accurate measurements in plant architecture and dry biomass that may be used to improve the accuracy of plant phenotyping.

scholarly journals A Role of Three-Dimensional (3D)-Reconstruction in the Classification of Lung Adenocarcinoma

2012 ◽  
Vol 35 (2) ◽  
pp. 79-84 ◽  
Author(s):  
Maristela L. Onozato ◽  
Veronica E. Klepeis ◽  
Yukako Yagi ◽  
Mari Mino-Kenudson
Keyword(s):  
Light Microscopy ◽  
3D Reconstruction ◽  
Lung Adenocarcinoma ◽  
Tumor Cells ◽  
New Technologies ◽  
Imaging System ◽  
Structural Information ◽  
Three Dimensional ◽  
Scanning System

Background: Three-dimensional (3D)-reconstruction from paraffin embedded sections has been considered laborious and time-consuming. However, the high-resolution images of large object areas and different fields of view obtained by 3D-reconstruction make one wonder whether it can add a new insight into lung adenocarcinoma, the most frequent histology type of lung cancer characterized by its morphological heterogeneity.Objective: In this work, we tested whether an automated tissue sectioning machine and slide scanning system could generate precise 3D-reconstruction of microanatomy of the lung and help us better understand and define histologic subtypes of lung adenocarcinoma.Methods: Four formalin-fixed human lung adenocarcinoma resections were studied. Paraffin embedded tissues were sectioned with Kurabo-Automated tissue sectioning machine and serial sections were automatically stained and scanned with a Whole Slide Imaging system. The resulting stacks of images were 3D reconstructed by Pannoramic Viewer software.Results: Two of the four specimens contained islands of tumor cells detached in alveolar spaces that had not been described in any of the existing adenocarcinoma classifications. 3D-reconstruction revealed the details of spatial distribution and structural interaction of the tumor that could hardly be observed by 2D light microscopy studies. The islands of tumor cells extended into a deeper aspect of the tissue, and were interconnected with each other and with the main tumor with a solid pattern that was surrounded by the islands. The finding raises the question whether the islands of tumor cells should be classified into a solid pattern in the current classification.Conclusion: The combination of new technologies enabled us to build an effective 3D-reconstruction of resected lung adenocarcinomas. 3D-reconstruction may help us refine the classification of lung adenocarcinoma by adding detailed spatial/structural information to 2D light microscopy evaluation.

3D Reconstruction and Visual Simulation of Double-Flowered Plants Based on Laser Scanning

2019 ◽  
Vol 33 (10) ◽  
pp. 1955013
Author(s):  
Dongna Cai ◽  
Zhi Li ◽  
Yongjian Huai
Keyword(s):  
Computer Vision ◽  
3D Reconstruction ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Morphological Structure ◽  
Digital Data ◽  
Visual Simulation ◽  
Cloud Data ◽  
Virtual Plant ◽  
Vision Simulation

Flower plants have become a major difficulty in virtual plant research because of their rich external morphological structure and complex physiological processes. Computer vision simulation provides powerful tools for exploring powerful biological systems and operating laws. In this paper, Chrysanthemum and Chinese rose, double flowers as the symbolic flowers of Beijing, are chosen as the study subject. On the basis of maximizing the protection of flower growth structure, an effective method based on laser scanning for three-dimensional (3D) reconstruction and visual simulation of flower plants is proposed. This method uses laser technology to scan the sample and store it as point cloud data. After applying a series of image analysis and processing techniques such as splicing, denoising, repairing and color correction, the digital data optimized by the sample is obtained accurately and efficiently, and a highly realistic 3D simulation model of the plant is formed. The results of the research indicate that it is a convenient research method for the 3D reconstruction of flower plants and computer vision simulation of virtual plants. It also provides an effective way for in-depth study of scientific experiments and digital protection of rare and endangered plants.

Nonrigid Registration of CLSM Images of Physical Sections with Discontinuous Deformations

2011 ◽  
Vol 17 (6) ◽  
pp. 923-936 ◽  
Author(s):  
Jan Michálek ◽  
Martin Čapek ◽  
Lucie Kubínová
Keyword(s):  
3D Reconstruction ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Iterative Solution ◽  
Brightness Distribution ◽  
Laser Scanning Microscopy ◽  
Confocal Laser ◽  
Regularization Term ◽  
Tv Regularization ◽  
Image Pairs

AbstractWhen biological specimens are cut into physical sections for three-dimensional (3D) imaging by confocal laser scanning microscopy, the slices may get distorted or ruptured. For subsequent 3D reconstruction, images from different physical sections need to be spatially aligned by optimization of a function composed of a data fidelity term evaluating similarity between the reference and target images, and a regularization term enforcing transformation smoothness. A regularization term evaluating the total variation (TV), which enables the registration algorithm to account for discontinuities in slice deformation (ruptures), while enforcing smoothness on continuously deformed regions, was proposed previously. The function with TV regularization was optimized using a graph-cut (GC) based iterative solution. However, GC may generate visible registration artifacts, which impair the 3D reconstruction. We present an alternative, multilabel TV optimization algorithm, which in the examined samples prevents the artifacts produced by GC. The algorithm is slower than GC but can be sped up several times when implemented in a multiprocessor computing environment. For image pairs with uneven brightness distribution, we introduce a reformulation of the TV-based registration, in which intensity-based data terms are replaced by comparison of salient features in the reference and target images quantified by local image entropies.

A New Method for 3D Reconstruction of Headlight Contour

2013 ◽  
Vol 321-324 ◽  
pp. 862-867
Author(s):  
Fei Tao ◽  
Ping An Mu ◽  
Shu Guang Dai ◽  
Jia Xing Shen
Keyword(s):  
3D Reconstruction ◽  
Laser Scanning ◽  
Measurement Techniques ◽  
Three Dimensional ◽  
Contour Detection ◽  
Transformation Model ◽  
Laser Source ◽  
Reconstruction Method ◽  
Matching Effect ◽  
Geometry Model

This paper put forward a 3D reconstruction method of the headlight contours based on laser scanning technology and robotics. Firstly, according to the present three-dimensional measurement techniques, the article put forward a set of headlight contour detection method based on the analytic geometry model and the line laser source scanning principle. It establishes a 3D scanning model and coordinate transformation model for 3D reconstruction of the headlight contour. Secondly, according to the demanding accuracy it structures the 3D reconstruction system. Finally it realizes the 3D reconstruction of the headlight contour based on the method, and the result is tested and evaluated matching effect, the result shows that can effectively realize the 3D reconstruction of headlight contour and the method has a good stability.

scholarly journals Novel 3D Imaging Systems for High-Throughput Phenotyping of Plants

2021 ◽  
Vol 13 (11) ◽  
pp. 2113
Author(s):  
Tian Gao ◽  
Feiyu Zhu ◽  
Puneet Paul ◽  
Jaspreet Sandhu ◽  
Henry Akrofi Doku ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
High Throughput ◽  
Imaging System ◽  
Point Clouds ◽  
Imaging Systems ◽  
Phenotypic Traits ◽  
Reconstruction Algorithms ◽  
High Quality ◽  
3D Point Clouds ◽  
High Throughput Phenotyping

The use of 3D plant models for high-throughput phenotyping is increasingly becoming a preferred method for many plant science researchers. Numerous camera-based imaging systems and reconstruction algorithms have been developed for the 3D reconstruction of plants. However, it is still challenging to build an imaging system with high-quality results at a low cost. Useful comparative information for existing imaging systems and their improvements is also limited, making it challenging for researchers to make data-based selections. The objective of this study is to explore the possible solutions to address these issues. We introduce two novel systems for plants of various sizes, as well as a pipeline to generate high-quality 3D point clouds and meshes. The higher accuracy and efficiency of the proposed systems make it a potentially valuable tool for enhancing high-throughput phenotyping by integrating 3D traits for increased resolution and measuring traits that are not amenable to 2D imaging approaches. The study shows that the phenotype traits derived from the 3D models are highly correlated with manually measured phenotypic traits (R2 > 0.91). Moreover, we present a systematic analysis of different settings of the imaging systems and a comparison with the traditional system, which provide recommendations for plant scientists to improve the accuracy of 3D construction. In summary, our proposed imaging systems are suggested for 3D reconstruction of plants. Moreover, the analysis results of the different settings in this paper can be used for designing new customized imaging systems and improving their accuracy.

Micron-scale phenotyping quantification and three-dimensional microstructure reconstruction of vascular bundles within maize stalks based on micro-CT scanning

2017 ◽  
Vol 44 (1) ◽  
pp. 10 ◽  
Author(s):  
Jianjun Du ◽  
Ying Zhang ◽  
Xinyu Guo ◽  
Liming Ma ◽  
Meng Shao ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Spatial Configuration ◽  
Three Dimensional ◽  
Ct Scanning ◽  
Phenotypic Traits ◽  
Vascular Bundles ◽  
Micro Computed Tomography ◽  
Cross Sectional ◽  
Imaging Device ◽  
Maize Stalks

Vascular bundles within maize (Zea mays L.) stalks play a key role in the mechanical support of plant architecture as well as in water and nutrient transportation. Convenient and accurate phenotyping of vascular bundles may help phenotypic identification of germplasm resources for breeding. Based on practical sample preparation procedures for maize stalks, we acquired serials of cross-sectional images using a micro-computed tomography (CT) imaging device. An image processing pipeline dedicated to the phenotyping of vascular bundles was also developed to automatically segment and validate vascular bundles from the cross-sectional images of maize stalks, from which phenotypic traits of vascular bundles, i.e. number, area, and spatial distribution, were calculated. More profound quantification of spatial distribution was given as area ratio of vascular bundles, which described the distribution of vascular bundles associated with the centroid of maize stalks. In addition, three-dimensional visualisation was performed to reveal the spatial configuration and distribution of vascular bundles. The proposed method significantly improves computation accuracy for the phenotypic traits of vascular bundles compared with previous methods, and is expected to be useful for illustrating relationships between phenotypic traits of vascular bundles and their function.

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