Image Collection System Research Articles

Night Lighting Fault Detection Based on Improved YOLOv5

Night lighting is essential for urban life, and the occurrence of faults can significantly affect the presentation of lighting effects. Many reasons can cause lighting faults, including the damage of lamps and circuits, and the typical manifestation of the faults is that the lights do not light up. The current troubleshooting mainly relies on artificial visual inspection, making detecting faults difficult and time-consuming. Therefore, it is necessary to introduce technical means to detect lighting faults. However, current research on lighting fault detection mainly focuses on using non-visual methods such as sensor data analysis, which has the disadvantages of having a high cost and difficulty adapting to large-scale fault detection. Therefore, this study mainly focuses on solving the problem of the automatic detection of night lighting faults using machine vision methods, especially object detection methods. Based on the YOLOv5 model, two data fusion models have been developed based on the characteristics of lighting fault detection inverse problems: YOLOv5 Channel Concatenation and YOLOv5 Image Fusion. Based on the dataset obtained from the developed automatic image collection and annotation system, the training and evaluation of these three models, including the original YOLOv5, YOLOv5 Channel Concatenation, and YOLOv5 Image Fusion, have been completed. Research has found that applying complete lighting images is essential for the problem of lighting fault detection. The developed Image Fusion model can effectively fuse information and accurately detect the occurrence and area of faults, with a mAP value of 0.984. This study is expected to play an essential role in the intelligent development of urban night lighting.

Randomized Double-Blind Placebo-Controlled Supplementation with Standardized Terminalia chebula Fruit Extracts Reduces Facial Sebum Excretion, Erythema, and Wrinkle Severity

Terminalia chebula (TC) is a medicinal plant that exhibits antioxidant, anti-inflammatory, and antibacterial properties and that is widely used in Ayurveda and herbal formulations. However, the skin effects of TC as an oral supplement have not been studied. The objective of this study is to determine if oral TC fruit extract supplementation can modulate the skin's sebum production and reduce the appearance of wrinkles. A prospective double-blind placebo-controlled study was conducted on healthy females aged 25-65. Subjects were supplemented with an oral placebo or Terminalia chebula (250 mg capsule, Synastol TC) capsules twice daily for eight weeks. A facial image collection and analysis system was used to assess the facial appearance of wrinkle severity. Standardized, non-invasive tools were used to measure facial moisture, sebum production, transepidermal water loss, melanin index and erythema index. For those who had a baseline sebum excretion rate >80 ug/cm2, TC supplementation produced a significant decrease in forehead sebum excretion rate compared to the placebo at four weeks (-17 decrease vs. 20% increase, p = 0.07) and at eight weeks (-33% decrease vs. 29% increase, p < 0.01). Cheek erythema decreased by 2.2% at eight weeks, while the placebo treatment increased cheek erythema by 1.5% (p < 0.05). Facial wrinkles decreased by 4.3% in the TC group and increased by 3.9% in the placebo group after eight weeks of supplementation (p < 0.05). TC supplementation reduces facial sebum and improves the appearance of wrinkles. Future studies should consider evaluating oral TC as adjuvant therapy for acne vulgaris.

Effect of proton beam irradiation on the tracking efficiency of CMOS image sensors

A star tracker provides accurate space positioning and reference for satellites, intercontinental strategic missiles, and other spacecrafts. However, the main imaging unit of the star sensor – the image sensor – is affected by the space radiation environment and, in turn, affects the precision with which the star is located by the star tracker. In this study, the parameter degradation of a CMOS image sensor (CIS) after proton irradiation with different fluences was investigated. An outfield test platform for star map collection was built using the star sensor lens and image collection system. The influence of dark current, dark-current nonuniformity, and photo-response nonuniformity of the irradiated CIS on the star diagonal distance measurement error and star-point centroid position detection accuracy was studied. The results showed that with increasing proton fluences, the CIS noise increased, leading to an increase in the error in the measured diagonal distance of the star and a decrease in the star’s position detection accuracy. Among these parameters, the dark current plays the greatest role in influencing the measurement accuracy of the star tracker. Furthermore, when a tracker is exposed to space radiation with fluences that are same as those used in this experiment, it is beneficial to reduce the integration time. This reduction in the time will decrease the noise and improve the position measurement accuracy.

Practical use of a multicenter clinical research support system connected to electronic medical records

BackgroundElectronic medical records (EMRs) are widely used, but in many cases, they are used within a network physically separated from the Internet. Multicenter clinical studies use Internet-connected electronic data capture (EDC) systems to collect data, where data entered into the EMR are manually transcribed into the EDC system. In addition, medical images for clinical research are also collected manually. Variations in EMRs and differing data structures among vendors hamper the use of data for clinical research. MethodsWe solved this problem by developing a network infrastructure for clinical research between Osaka University Hospital and affiliated hospitals in the Osaka area and introducing a clinical data collection system (CDCS). In each hospital's EMR network, we implemented a CRF reporter that accumulated data for clinical research using a template and then sent the data to a management server in the Osaka University Hospital Data Center. To organize the patient profile data and clinical laboratory data stored in each EMR for use in clinical research, the data are retrieved from the template by an interface module developed by each vendor, according to our common data output interface specification. The data entered into the CRF reporter template for clinical research are also recorded in the EMR progress notes and sent to the data management server. This network infrastructure can also be used as a medical image collection system that automatically collects images for research from PACS at each hospital. These systems are managed under common subject numbers issued by the CDCS. ResultsA network infrastructure was established among 19 hospitals, and a CRF reporter was incorporated into the EMR. A medical image transfer system was introduced in 13 hospitals. Since 2013, 28 clinical studies have been conducted using this system, and data for 9,987 cases have been collected as of December 31, 2020. ConclusionIncorporating a CRF reporter with medical image transfer system into the EMR has proven useful for collecting research data.

Size Detection Method of Embedded Ball Based on Aviation Bearing Image

In the aerospace industry, bearing is widely used in various rotating machinery. The performance of bearing affects the operation of the whole machinery and even aviation equipment. The wrongly assembled ball due to size is an important reason for unqualified bearing. To solve this problem, an accurate ball detection method based on the bearing image is proposed. Firstly, according to the imaging characteristics of bearing and light propagation characteristics, an image collection system based on the coaxial light source is designed. Then, aiming at the problem that the embedded ball is occluded by the bearing ring and the cage, only partial ball in the narrow gap can be used to predict the full ball and the high-precision requirement of ball detection, a ball segmentation model based on DeepLab v3+ network is used to segment the local ball, and CBAM is added in the Xception network of the original network. According to the characteristics of the segmentation result, a circle detection algorithm based on circle fitting evaluation designed for incomplete short arc is proposed. Finally, according to the detection results, judge whether the bearing is qualified or not and evaluate the feasibility of this method. Experimental results show that the ball detection accuracy is about 27 microns, and the wrongly assembled ball with a size difference of only 198 microns can be distinguished. The false detection rate of unqualified bearing is 1%. As the last line of defense of bearing quality inspection, this method can achieve zero false detection rate of unqualified bearing in the industry.

An Automatic Image Collection System for Multicenter Clinical Studies.

The acquisition of medical images from multiple medial institutions has become important for high-quality clinical studies. In recent years, electronic data submission has enabled the transmission of image data to independent institutions more quickly and easily than before. However, the selection, anonymization, and transmission of medical images still require human resources in the form of clinical research collaborators. In this study, we developed an image collection system that works with the electronic data capture (EDC) system. In this image collection system, medical images are selected based on EDC input information, patient ID is anonymized to a subject ID issued by the EDC, and the selected anonymized images are transferred to the research institute without human intervention. In the research institute, clinical information registered by the EDC and clinical images collected by the image collection system are managed by the same subject ID and can be used for clinical studies. In October 2019, our image collection system was introduced to 13 medical institutions and has now begun collecting medical images from the in-hospital picture archiving and communication system (PACS) of those institutions.

Design of airborne target tracking accelerator based on KCF

The on-board target tracking of unmanned aerial vehicle (UAV) relies on on-board computer to process the collected ground image information, and then use the target tracking algorithm to achieve the target tracking function, which provides the user with target position, trajectory and other information. UAVs are limited by load and power consumption. Due to the high resolution and frame rate of UAV's image collection system, traditional target tracking platforms cannot meet the requirements. As a result, the real-time nature of the tracking platform urgently needs to be resolved. This study designs and implements the airborne ground target tracking accelerator for UAV. The kernelised correlation filters (KCFs) algorithm with low computational complexity and precision is selected to achieve the airborne ground target tracking function and its performance bottleneck is analysed. In order to improve the real-time performance of the tracking task processing, the ZYNQ platform based on ARM and field programmable gate arrays is chosen to achieve the hardware acceleration of the KCF algorithm. The KCF algorithm is implemented in hardware using the high-level synthesis technology, and a high-speed data transmission link is established. Experiments show that the design can achieve a tracking rate of more than 30 FPS under 960 × 540 resolution, which meets the real-time requirements of UAV target tracking task.

Field Investigation of Clay Balls in Full-Depth Asphalt Pavement.

Clay ball is a pavement surface defect which refers to a clump in which clay or dirt is mixed with hot asphalt mixture. Clay ball is typically caused by a combination of aggregate contamination of clay or soil, high aggregate moisture, and low production temperature at the asphalt plant. It usually appears a few weeks or months after paving under traffic load, after being liquefied and knocked from the pavement surface. Clay balls can be the source of potholing, raveling, and other issues such as moisture infiltration and reduced ride quality. This paper presents an investigation of the clay balls on US-31 one winter after construction in Hamilton County, Indiana. In order to understand the pavement condition, their severity was measured using both visual observation and infrared image collection system. In addition, a clay ball amount, its distribution pattern, and cores condition were evaluated. A precipitation effect on clay ball formation was investigated for finding a cause of the clay balls. The investigation found that infrared image collection system was appropriate in detecting the clay balls. The clay balls were elliptic in shape with 2.5 cm to 10 cm in diameter, and the maximum clay ball depth was almost penetrating the entire surface course. It was also found that the asphalt paving on the raining days or right after raining could increase the potential of clay balls. Monitoring of aggregate moisture during construction on or after raining days should be able to reduce the risk of clay balls.

Online Inspection Method of Defect Dimension of Stainless Steel Precision Blanking Sheet Contour

In this study, a new method of online inspection of contour defects is proposed for stainless steel precision blanking sheet to address problems in the use of the current method to obtain detect information: the recognition system is complex, and the measurement error of defect dimension is large. The images of defect blanking sheet are obtained by the established image collection system. The results of image analysis show that the defect contour of blanking sheet has the correspondence and similarity characteristics. An improved sequential similarity detection algorithm and the measurement algorithm are developed. The measurement experiments show that the online inspection system is stable and reliable, and the maximum measurement error is 0.0362mm. The results of this study will lay a foundation for the online inspection of precision machining.

A Rapid UAV Image Georeference Algorithm Developed for Emergency Response

The image collection system based on the unmanned aerial vehicle plays an important role in the postearthquake response and disaster investigation. In the postearthquake response period, for hundreds of image stitching or 3D model reconstruction, the traditional UAV image processing methods may take one or several hours, which need to be improved on the efficiency. To solve this problem, the UAV image rapid georeference method for postearthquake is proposed in this paper. Firstly, we discuss the rapid georeference model of UAV images and then adopt the world file designed and developed by ESRI to organize the georeferenced image data. Next, the direct georeference method based on the position and attitude data collected by the autopilot system is employed to compute the upper-left corner coordinates of the georeferenced images. For the differences of image rotation manners between the rapid georeference model and the world file, the rapid georeference error compensation model from the image rotation is considered in this paper. Finally, feature extraction and feature matching for UAV images and referenced image are used to improve the accuracy of the position parameters in the world file, which will reduce the systematic error of the georeferenced images. We use the UAV images collected from Danling County and Beichuan County, Sichuan Province, to implement the rapid georeference experiments employing different types of UAV. All the images are georeferenced within three minutes. The results show that the algorithm proposed in this paper satisfies the time and accuracy requirements of postearthquake response, which has an important application value.

Preliminary Study of UAS Equipped with Thermal Camera for Volcanic Geothermal Monitoring in Taiwan.

Thermal infrared cameras sense the temperature information of sensed scenes. With the development of UASs (Unmanned Aircraft Systems), thermal infrared cameras can now be carried on a quadcopter UAV (Unmanned Aircraft Vehicle) to appropriately collect high-resolution thermal images for volcanic geothermal monitoring in a local area. Therefore, the quadcopter UAS used to acquire thermal images for volcanic geothermal monitoring has been developed in Taiwan as part of this study to overcome the difficult terrain with highly variable topography and extreme environmental conditions. An XM6 thermal infrared camera was employed in this thermal image collection system. The Trimble BD970 GNSS (Global Navigation Satellite System) OEM (Original Equipment Manufacturer) board was also carried on the quadcopter UAV to gather dual-frequency GNSS observations in order to determine the flying trajectory data by using the Post-Processed Kinematic (PPK) technique; this will be used to establish the position and orientation of collected thermal images with less ground control points (GCPs). The digital surface model (DSM) and thermal orthoimages were then produced from collected thermal images. Tests conducted in the Hsiaoyukeng area of Taiwan’s Yangmingshan National Park show that the difference between produced DSM and airborne LIDAR (Light Detection and Ranging) data are about 37% between −1 m and 1 m, and 66% between −2 m and 2 m in the area surrounded by GCPs. As the accuracy of thermal orthoimages is about 1.78 m, it is deemed sufficient for volcanic geothermal monitoring. In addition, the thermal orthoimages show some phenomena not only more globally than do the traditional methods for volcanic geothermal monitoring, but they also show that the developed system can be further employed in Taiwan in the future.

Design of Automatic Mildew Image Detection System for Corn Grain

Using image processing technology, designed a corn grain mildew fast detection system. It could discriminate the mildew grain on the basis of the grain surface features, such as color features, morphological characteristics, and texture characteristics. Equipment mainly included three parts: mechanical transmission device, the image collection system, image processing software. By using the theory of corn seeder for reference, corn seed metering device discharged corn grain in uniform along the conveyor belt. Device adopted run 3 seconds stop 1 second cycle works. During the suspended period, completed image information acquisition, transmission and processing, by CCD cameras, lenses, camera obscura, computer, gigabit ethernet cable. It can avoid the overlap of grains, which could measure more grain at the same time. Using MATLAB GUI module to program image processing software, for automatic processing of corn grain sample figure. Maize kernels would be detected which occur mouldy, and then doing statistics of the mildew rate, detection accuracy could reach 90%.

Pi Logger : 스마트 팜 보급 확대를 위한 저가형 온실 영상 및 환경 데이터 수집 시스템

Pi Logger : 스마트 팜 보급 확대를 위한 저가형 온실 영상 및 환경 데이터 수집 시스템

A Pilot Study on the Development of Remote Quality Control of Digital Mammography Systems in the NHS Breast Screening Programme

In the UK, physicists and radiographers perform routine quality control (QC) of digital mammography equipment at daily, weekly and monthly intervals. The tests performed and tolerances are specified by standard protocols. The manual nature of many of the tests introduces variability due to the positioning of regions of interest (ROIs) and can be time consuming. The tools on workstations provided by manufacturers limit the range of analysis that radiographers can perform and do not allow for a standard set of tools and analysis because they are specific to a given manufacturer. Automated software provides a means of reducing the variability in the analysis and also provides the possibility of additional, more complex analysis than is currently performed on the daily, weekly and monthly checks by radiographers. To this end, a set of tools has been developed to analyse the routine images taken by radiographers. As well as automatically reproducing the usual measurements by radiographers more complex analysis is provided. A QC image collection system has been developed which automatically routes QC data from a clinical site to a centralised server for analysis. A Web-based interface has been created that allows the users to view the performance of the mammographic equipment. The pilot system obtained over 3000 QC images from seven X-ray units at a single screening centre over 2 years. The results show that these tools and methods of analysis can highlight changes in a detector over time that may otherwise go unnoticed with the conventional analysis.

Research on Keyhole Diameter’s Vision Measurement Based on Parallel Technology

A keyhole diameter of the cartridge’s measurement based on machine vision is a part of the cartridge’s geometry measurement system, according to the system requirements, to complete the measurement within 5 seconds. A Image Collection System was constructed using computer, CCD camera, LED source, meanwhile a measurement system was compiled by C# on VS2010 platform based on machine vision. Use the Otsu algorithm to extracts the keyhole’s edge and near the pixels in order to reduce the computational Canny operator, and use parallel computing in the Canny operator to improve computing speed purposes. Use QueryPerformanceCounter timer for each module timing Canny operator, Canny operator improved computation time is reduced from the original 6s to nearly a hundred ms improved. Meet the time requirements of cartridge geometry measurement system, and other machine vision in which the project can be widely used.

Self-Organizing Feature Extraction Method for the High-Voltage Discharge Fault in Ultraviolet Imaging Detection System

An ultraviolet detecting system for electrical faults is designed and built to locate the fault precisely and classify its pattern level as few studies have been done on. Self-organizing feature extraction method devotes itself to fault state recognition approach in high-voltage discharge. The established system including the filter system, image collection system, image preprocessing system, feature extraction, and pattern recognition could identify and classify device faults and operation conditions accurately tested by simulation.

基于Harris角点的矩形检测

To recognize and detect a rectangle rapidly and accurately,an image collection system was established and a rapid detection algorithm for rectangles was proposed based on Harris corner detection algorithm.First,the L-shaped corner points were selectively recognized from all kinds of corner points in the detecting image by improving the traditional Harris corner detection algorithm,and the position accuracy of corner points was promoted by sub-pixel post-processing.Then,according to the obtained high-precision angular position information,some parallel straight line segment pairs with equal length were grouped and the perpendicular parallel line segment pairs with four overlap corner points were matched,by which the four sides of a rectangle were obtained.Furthermore,all the rectangle elements were detected in the processed image.In order to improve the accuracy and reliability of the rectangular recognition algorithm,the identifying criterion of the pseudo rectangular graphic elements was provided.Finally,the sensor performance testing experiments were carried out.Experimental results indicate that the rectangular recognition speed of Harris corner point algorithm is 8.5times faster than that of Hough algorithm,and the rectangular image recognition maximum position error is 0.4pixel.The Harris corner rectangle detection method has strong anti-interference capability and stability and can meet thehigh real-time and precision detection requirements of industrial application.

Research on Marine Radar Image Collection Technology Based on OpenCV

Marine radar image collection technology has been applied in many fileds. It has been a research focus at home and abroad for a long time. This paper proposes an architecture of marine radar image collection system based on Sperry radar, HPX Rader Information Board, OpenCV, SPX Function Library. And implementation of key technologies was diccussed from three aspects, includ-ing radar image display, collection and clear functions. This system has worked well in practice.

Experimental Research of Impinging Spray with Basic Impinging Scheme

Visualization experimental system of impinging spray including high-pressure vessel, oil supply system, light path system, image collection and treatment system and control system was designed, and the visualization experiments of basic impinging schemes of flat wall was carried out under existing conditions without laser. The effect of impinging distance on rebounding distance and diffusing area of dripping was analyzed. The results show that both of diffusing distance along the wall and distribution area linearly increased within a certain time under the same impinging distance. Both of diffusing distance along the wall and rebounding distance decreased with the increase in impinging distance.

基于ADV212的远程图像采集系统设计

To solve the problem of excessive demand for remote network bandwidth when transmit color high-definition image through ethernet,this article gives a compression and transmission solution based on the combination of JPEG2000 Video Codec ADV212 and a FPGA with control logic.This system use a Bayer Pattern CMOS image sensor as data source,use the ADV212 to achieve fast high-quality image compression,the FPGA implements the entire system control logic,such as configuration on the ADV212,pre-distribution image,driving ADV212 under its timing and package the compressed stream.The experiments show that the system can guarantee to receive the image having a high peak signal to noise ratio,long-term stability 36 Mbyte/s image input conditions,and the system is small and easy to use,low bandwidth consumption and the compression ratio is adjustable and so on.