Thallus morphology of two Antarctic foliose lichens evaluated by a digital optical microscopy approach ( Short Communication)

2016 ◽  
Vol 6 (1) ◽  
pp. 80-86 ◽  
Author(s):  
Rastislav Ošťádal ◽  
Jana Hazdrová
Keyword(s):  
Imaging System ◽  
Digital Camera ◽  
Image Data ◽  
Projection Area ◽  
Digital Microscopy ◽  
Diameter Increment ◽  
Lichen Thallus ◽  
Main Components ◽  
Processing Techniques ◽  
Water Holding

Digital microscopy is an emerging technique that combines the tools of classic light microscopy with a computerized imaging system. The main components of digital microscopy is image formation by optics of the system, image registration by a digital camera, saving of image data in a file format that enables advanced image analysis.In this paper, we bring first data on application of digital microscopy approach in lichen thallus morphology study. Two Antarctic lichen species (Xanthoria elegans, Umbilicaria decussata) with a foliose morphotype of their thallus were studied. Both experimental species had an irregularly round or eliptic shape of a thallus that enabled to measure its diameter. After magnifition, images were taken in dry and fully-hydrated state of thallus in order to evaluate hydration-dependent size changes in thallus size and structures. It has been demonstrated that hydration-dependent size increment depend on thallus size and particular part of thallus. Mean increment of thallus diameter reached 15.1% and 13.8% for X. elegans and U. decussata, respectively. Higher value of diameter increment (26 %) was found for the upper projection area of apothecia, fruiting bodies developed over the upper thallus surface of X. elegans. Size and volume increment in thallus parts is discussed as a consequence of water holding capacity of lichens, and a capability of lichens to hold intra- and extracellular water upon full hydration of a thallus. Finally, a potential of digital microscopy for future studies is discussed as well as some processing techniques such as e.g. metrics of profile lines through 3-D objects like apothecia.

Deep Learning Approaches for Whiteboard Image Quality Enhancement

2019 ◽  
Vol 2019 (1) ◽  
pp. 360-368
Author(s):  
Mekides Assefa Abebe ◽  
Jon Yngve Hardeberg
Keyword(s):  
Deep Learning ◽  
Image Quality ◽  
Image Data ◽  
Quality Enhancement ◽  
Network Architectures ◽  
Learning Approaches ◽  
Data Set ◽  
Image Quality Enhancement ◽  
Processing Techniques ◽  
White Balancing

Different whiteboard image degradations highly reduce the legibility of pen-stroke content as well as the overall quality of the images. Consequently, different researchers addressed the problem through different image enhancement techniques. Most of the state-of-the-art approaches applied common image processing techniques such as background foreground segmentation, text extraction, contrast and color enhancements and white balancing. However, such types of conventional enhancement methods are incapable of recovering severely degraded pen-stroke contents and produce artifacts in the presence of complex pen-stroke illustrations. In order to surmount such problems, the authors have proposed a deep learning based solution. They have contributed a new whiteboard image data set and adopted two deep convolutional neural network architectures for whiteboard image quality enhancement applications. Their different evaluations of the trained models demonstrated their superior performances over the conventional methods.

New Monitoring Strategy for the Quality Control in the Processing Practice of Scutellariae Radix

2020 ◽  
Vol 16 (3) ◽  
pp. 303-311
Author(s):  
Qi Huang ◽  
Chunsong Cheng ◽  
Lili Li ◽  
Daiyin Peng ◽  
Cun Zhang
Keyword(s):  
Quality Control ◽  
Monitoring Strategy ◽  
Scutellariae Radix ◽  
Chromatographic Fingerprints ◽  
New Strategy ◽  
Processed Products ◽  
Main Components ◽  
Processing Techniques ◽  
Multivariate Monitoring

Background: Scutellariae Radix (Huangqin) is commonly processed into 3 products for different clinical applications. However, a simple analytical method for quality control has rarely been reported to quickly estimate the degree of processing Huangqin or distinguish differently processed products or unqualified Huangqin products. Objective: To study a new strategy for quality control in the processing practice of Huangqin. Methods: Seven kinds of flavonoids that mainly exist in Huangqin were determined by HPLC-DAD. Chromatographic fingerprints were established to study the variation and discipline of the 3 processed products of Huangqin. PCA and OPLS-DA were used to classify differently processed products of Huangqin. Results: The results showed that baicalin and wogonoside were the main components in the crude and the alcohol Huangqin herb while baicalein and wogonin mainly existed in carbonized Huangqin. The results of mathematical statistics revealed that the processing techniques can make the quality of medicinal materials more uniform. Conclusion: This multivariate monitoring strategy is suitable for quality control in the processing of Huangqin.

scholarly journals UAV-Driven Structural Crack Detection and Location Determination Using Convolutional Neural Networks

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2650
Author(s):  
Daegyun Choi ◽  
William Bell ◽  
Donghoon Kim ◽  
Jichul Kim
Keyword(s):  
Visual Information ◽  
Crack Detection ◽  
Image Data ◽  
Image Processing Techniques ◽  
Location Determination ◽  
Aerial Vehicle ◽  
Using Data ◽  
Processing Techniques ◽  
Deep Learning Model ◽  
Structural Cracks

Structural cracks are a vital feature in evaluating the health of aging structures. Inspectors regularly monitor structures’ health using visual information because early detection of cracks on highly trafficked structures is critical for maintaining the public’s safety. In this work, a framework for detecting cracks along with their locations is proposed. Image data provided by an unmanned aerial vehicle (UAV) is stitched using image processing techniques to overcome limitations in the resolution of cameras. This stitched image is analyzed to identify cracks using a deep learning model that makes judgements regarding the presence of cracks in the image. Moreover, cracks’ locations are determined using data from UAV sensors. To validate the system, cracks forming on an actual building are captured by a UAV, and these images are analyzed to detect and locate cracks. The proposed framework is proven as an effective way to detect cracks and to represent the cracks’ locations.

A Novel Method for Automated Tool Path Optimisation for CNC Machining Operations

2010 ◽  
Vol 166-167 ◽  
pp. 357-362
Author(s):  
Shahed Shojaeipour
Keyword(s):  
Tool Path ◽  
Target Location ◽  
Imaging System ◽  
Optimal Path ◽  
Digital Camera ◽  
Basic Program ◽  
Cnc Machining ◽  
Cnc Machine ◽  
Current Location ◽  
Tool Diameter

In this article, a new method for rapid tool movement in CNC machines is presented. Firstly, a single digital camera, installed on the Z-axis, captures the image of the workpiece on the work table. Image processing techniques, implemented using MATLAB, are then used to convert the image into a binary black and white image. This allows the locations of protruding edge sections on the workpiece, which could impede tool movement, to be identified. Quadtree decomposition is then performed on the binary image, and possible paths from the tool current location to its target location are found. These paths are then analysed based on the tool diameter clearance and the distance to the goal, and the shortest path with sufficient tool clearance is selected. A Visual Basic program then converts the selected path into G-code commands that provides instructions to the CNC machine tool such that this path is followed. With this method, the workpiece fixture location would not have to be precise as the imaging system would be able to automatically identify the target location with respect to the tool current location, along with the optimal path to reach it.

scholarly journals Bionic Birdlike Imaging Using a Multi-Hyperuniform LED Array

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4084
Author(s):  
Xin-Yu Zhao ◽  
Li-Jing Li ◽  
Lei Cao ◽  
Ming-Jie Sun
Keyword(s):  
Imaging System ◽  
Color Image ◽  
Digital Camera ◽  
Frame Rate ◽  
Digital Cameras ◽  
Structured Illumination ◽  
Pixel Resolution ◽  
Led Array ◽  
Frequency Aliasing ◽  
Imaging Sensors

Digital cameras obtain color information of the scene using a chromatic filter, usually a Bayer filter, overlaid on a pixelated detector. However, the periodic arrangement of both the filter array and the detector array introduces frequency aliasing in sampling and color misregistration during demosaicking process which causes degradation of image quality. Inspired by the biological structure of the avian retinas, we developed a chromatic LED array which has a geometric arrangement of multi-hyperuniformity, which exhibits an irregularity on small-length scales but a quasi-uniformity on large scales, to suppress frequency aliasing and color misregistration in full color image retrieval. Experiments were performed with a single-pixel imaging system using the multi-hyperuniform chromatic LED array to provide structured illumination, and 208 fps frame rate was achieved at 32 × 32 pixel resolution. By comparing the experimental results with the images captured with a conventional digital camera, it has been demonstrated that the proposed imaging system forms images with less chromatic moiré patterns and color misregistration artifacts. The concept proposed verified here could provide insights for the design and the manufacturing of future bionic imaging sensors.

Part Monitoring and Quality Assessment of Conformal Additive Manufacturing Using Image Reconstruction

2018 ◽  
Author(s):  
Michael D. Kutzer ◽  
Levi D. DeVries ◽  
Cooper D. Blas
Keyword(s):  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Digital Camera ◽  
Image Data ◽  
Digital Cameras ◽  
Public And Private ◽  
The Public ◽  
Fused Deposition ◽  
Complex Part ◽  
Deposition Modeling

Additive manufacturing (AM) technologies have become almost universal in concept development, prototyping, and education. Advances in materials and methods continue to extend this technology to small batch and complex part manufacturing for the public and private sectors. Despite the growing popularity of digital cameras in AM systems, use of image data for part monitoring is largely unexplored. This paper presents a new method for estimating the 3D internal structure of fused deposition modeling (FDM) processes using image data from a single digital camera. Relative transformations are established using motion capture, and the 3D model is created using knowledge of the deposition path coupled with assumptions about the deposition cross-section. Results show that part geometry can be estimated and visualized using the methods presented in this work.

A Robust Feature Points Matching Algorithm in 3D Optical Measuring System

2011 ◽  
Vol 383-390 ◽  
pp. 5193-5199 ◽  
Author(s):  
Jian Ying Yuan ◽  
Xian Yong Liu ◽  
Zhi Qiang Qiu
Keyword(s):  
3D Reconstruction ◽  
Digital Camera ◽  
Image Data ◽  
Epipolar Geometry ◽  
Bundle Adjustment ◽  
Measuring System ◽  
Feature Points ◽  
3 Dimensional ◽  
Feature Points Matching ◽  
Optical Measuring

In optical measuring system with a handheld digital camera, image points matching is very important for 3-dimensional(3D) reconstruction. The traditional matching algorithms are usually based on epipolar geometry or multi-base lines. Mistaken matching points can not be eliminated by epipolar geometry and many matching points will be lost by multi-base lines. In this paper, a robust algorithm is presented to eliminate mistaken matching feature points in the process of 3D reconstruction from multiple images. The algorithm include three steps: (1) pre-matching the feature points using constraints of epipolar geometry and image topological structure firstly; (2) eliminating the mistaken matching points by the principle of triangulation in multi-images; (3) refining camera external parameters by bundle adjustment. After the external parameters of every image refined, repeat step (1) to step (3) until all the feature points been matched. Comparative experiments with real image data have shown that mistaken matching feature points can be effectively eliminated, and nearly no matching points have been lost, which have a better performance than traditonal matching algorithms do.

scholarly journals Imaging Analysis by Digital Camera for Separating Broiler Breast Meat with Low Water-Holding Capacity

2017 ◽  
Vol 54 (3) ◽  
pp. 253-261 ◽  
Author(s):  
Pensiri Kaewthong ◽  
Kriangkrai Waiyagan ◽  
Saowakon Wattanachant
Keyword(s):  
Digital Camera ◽  
Water Holding Capacity ◽  
Imaging Analysis ◽  
Breast Meat ◽  
Broiler Breast ◽  
Water Holding

Real-Time Analysis of Human Body Parts and Gesture-Activity Recognition in 3D

2011 ◽  
pp. 130-174
Author(s):  
Burak Ozer ◽  
Tiehan Lv ◽  
Wayne Wolf
Keyword(s):  
Real Time ◽  
Activity Recognition ◽  
Visual Processing ◽  
Visual Analysis ◽  
Three Dimensional ◽  
Real Time Processing ◽  
Visual Reconstruction ◽  
Three Dimensional Models ◽  
Main Components ◽  
Processing Techniques

This chapter focuses on real-time processing techniques for the reconstruction of visual information from multiple views and its analysis for human detection and gesture and activity recognition. It presents a review of the main components of three-dimensional visual processing techniques and visual analysis of multiple cameras, i.e., projection of three-dimensional models onto two-dimensional images and three-dimensional visual reconstruction from multiple images. It discusses real-time aspects of these techniques and shows how these aspects affect the software and hardware architectures. Furthermore, the authors present their multiple-camera system to investigate the relationship between the activity recognition algorithms and the architectures required to perform these tasks in real time. The chapter describes the proposed activity recognition method that consists of a distributed algorithm and a data fusion scheme for two and three-dimensional visual analysis, respectively. The authors analyze the available data independencies for this algorithm and discuss the potential architectures to exploit the parallelism resulting from these independencies.

The Design of High-Speed CMOS Imaging System Based on SOPC Technology

2010 ◽  
Vol 39 ◽  
pp. 523-528
Author(s):  
Xin Hua Yang ◽  
Yuan Yuan Shang ◽  
Da Wei Xu ◽  
Hui Zhuo Niu
Keyword(s):  
High Speed ◽  
Imaging System ◽  
Image Acquisition ◽  
Image Data ◽  
Image Sensor ◽  
Acquisition System ◽  
Storage Unit ◽  
Data Encoding ◽  
Acquisition Speed ◽  
Image Acquisition System

This paper introduces a design of a high-speed image acquisition system based on Avalon bus which is supported with SOPC technology. Some peripherals embedded in Avalon bus were customized and utilized in this system, such as imaging unit, decoding unit and storage unit, and these improved the speed of the whole imaging system. The data is compressed to three-fourths of the original by the decoding unit. A custom DMA is designed for moving the image data to the two caches of the SDRAM. This approach discards the method that FIFO must be put up in the traditional data acquisition system. And therefore, it reduced the CPU’s task for data moving. At the same time, the image acquisition and the data transmission can complete a parallel job. Finally, the design is worked on the high-speed image acquisition system which is made up of 2K*2K CMOS image sensor. And it improved the image acquisition speed by three ways: data encoding, custom DMA controller and the parallel processing.

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