• Title/Summary/Keyword: image assessment

Search Result 1,139, Processing Time 0.024 seconds

Bridge Inspection and condition assessment using Unmanned Aerial Vehicles (UAVs): Major challenges and solutions from a practical perspective

  • Jung, Hyung-Jo;Lee, Jin-Hwan;Yoon, Sungsik;Kim, In-Ho
    • Smart Structures and Systems
    • /
    • v.24 no.5
    • /
    • pp.669-681
    • /
    • 2019
  • Bridge collapses may deliver a huge impact on our society in a very negative way. Out of many reasons why bridges collapse, poor maintenance is becoming a main contributing factor to many recent collapses. Furthermore, the aging of bridges is able to make the situation much worse. In order to prevent this unwanted event, it is indispensable to conduct continuous bridge monitoring and timely maintenance. Visual inspection is the most widely used method, but it is heavily dependent on the experience of the inspectors. It is also time-consuming, labor-intensive, costly, disruptive, and even unsafe for the inspectors. In order to address its limitations, in recent years increasing interests have been paid to the use of unmanned aerial vehicles (UAVs), which is expected to make the inspection process safer, faster and more cost-effective. In addition, it can cover the area where it is too hard to reach by inspectors. However, this strategy is still in a primitive stage because there are many things to be addressed for real implementation. In this paper, a typical procedure of bridge inspection using UAVs consisting of three phases (i.e., pre-inspection, inspection, and post-inspection phases) and the detailed tasks by phase are described. Also, three major challenges, which are related to a UAV's flight, image data acquisition, and damage identification, respectively, are identified from a practical perspective (e.g., localization of a UAV under the bridge, high-quality image capture, etc.) and their possible solutions are discussed by examining recently developed or currently developing techniques such as the graph-based localization algorithm, and the image quality assessment and enhancement strategy. In particular, deep learning based algorithms such as R-CNN and Mask R-CNN for classifying, localizing and quantifying several damage types (e.g., cracks, corrosion, spalling, efflorescence, etc.) in an automatic manner are discussed. This strategy is based on a huge amount of image data obtained from unmanned inspection equipment consisting of the UAV and imaging devices (vision and IR cameras).

Aero-optical transmitting effect in the compressible mixing layer

  • Ma, Handong;Gan, Caijun;Li, Lang
    • International Journal of Aerospace System Engineering
    • /
    • v.2 no.2
    • /
    • pp.79-82
    • /
    • 2015
  • The handicap for investigating the aero-optical effect focuses on the accurate prediction on the index refraction fluctuation or density fluctuation. In recent years, with the development of CFD techniques and optical experimental techniques, the comprehension have developed on the aero-optical transmitting effect in many kinds of complex flow. This study mainly introduces the optical aberration in compressible mixing layer. And then the debates about the mechanism of aero-optical effects and assessment of image blur also present.

Application of a newly developed software program for image quality assessment in cone-beam computed tomography

  • de Oliveira, Marcus Vinicius Linhares;Santos, Antonio Carvalho;Paulo, Graciano;Campos, Paulo Sergio Flores;Santos, Joana
    • Imaging Science in Dentistry
    • /
    • v.47 no.2
    • /
    • pp.75-86
    • /
    • 2017
  • Purpose: The purpose of this study was to apply a newly developed free software program, at low cost and with minimal time, to evaluate the quality of dental and maxillofacial cone-beam computed tomography (CBCT) images. Materials and Methods: A polymethyl methacrylate (PMMA) phantom, CQP-IFBA, was scanned in 3 CBCT units with 7 protocols. A macro program was developed, using the free software ImageJ, to automatically evaluate the image quality parameters. The image quality evaluation was based on 8 parameters: uniformity, the signal-to-noise ratio (SNR), noise, the contrast-to-noise ratio (CNR), spatial resolution, the artifact index, geometric accuracy, and low-contrast resolution. Results: The image uniformity and noise depended on the protocol that was applied. Regarding the CNR, high-density structures were more sensitive to the effect of scanning parameters. There were no significant differences between SNR and CNR in centered and peripheral objects. The geometric accuracy assessment showed that all the distance measurements were lower than the real values. Low-contrast resolution was influenced by the scanning parameters, and the 1-mm rod present in the phantom was not depicted in any of the 3 CBCT units. Smaller voxel sizes presented higher spatial resolution. There were no significant differences among the protocols regarding artifact presence. Conclusion: This software package provided a fast, low-cost, and feasible method for the evaluation of image quality parameters in CBCT.

CT and MRI Image Fusion Reproducibility and Dose Assessment on Treatment Planning System (치료계획시스템에서 전산화단층촬영과 자기공명영상의 영상융합 재현성 및 선량평가)

  • Choi, Jae-Hyock;Park, Cheol-Soo;Seo, Jeong-Min;Cho, Jae-Hwan;Choi, Cheon-Woong
    • Journal of the Korean Magnetics Society
    • /
    • v.24 no.6
    • /
    • pp.191-196
    • /
    • 2014
  • The purpose of this study is to evaluate the reproducibility and usefulness of an image through the fusion of the computed tomography image and the magnetic resonance image by using a self-produced phantom when planning the treatment, and also to compare and analyze the target dose on the acquired image. The size of small hole and the reproducibility of capacity existed in the phantom on the image of the phantom obtained by the computed tomography and the magnetic resonance image of the phantom scanning with different intensity of magnetic field are compared, and the change of dose in the random target is compared and analyzed.

Quantitative Evaluation of Image Quality using Automatic Exposure Control & Sensitivity in the Digital Chest Image (디지털 흉부영상에서 자동노출제어 및 감도변화를 이용한 영상품질의 정량적인 평가)

  • Lee, Jin-Soo;Ko, Seong-Jin;Kang, Se-Sik;Kim, Jung-Hoon;Kim, Dong-Hyun;Kim, Changsoo
    • The Journal of the Korea Contents Association
    • /
    • v.13 no.8
    • /
    • pp.275-283
    • /
    • 2013
  • The patient radiation dose is different depending on selection of Ion chamber when taking Chest PA which using AEC. In this paper, we studied acquiring the best diagnostic images according to selection of Ion chamber on AEC mode as well as minimizing patient radiation dose. Experimental methods were selection of Ion chamber and change of sensitivity under the same conditions as Chest PA projection. At AEC mode, two upper ion chambers sensors and one lower ion chamber sensor were divided into 7 cases according to selection of on/off. after measuring five times respectively, we obtained average value and calculated exposure dose. Image assessment was done with measured Modulation Transfer Function, Peak Signal to Noise Ratio, Root Mean Square, Signal to Noise Ratio, Contrast to Noise Ratio, Mean to Standard deviation Ratio respectively. In exposure assessment results, selection of two upper chambers was the lowest. In resolution assessment results, image of two upper chambers had the second high spatial frequency at sensitivity at 625(High) was 1.343 lp/mm. RMS value of image selecting two upper chambers was low secondly. SNR, CNR, MSR were the high value secondly. As the sensitivity was increased, radiation dose was decreased but better image could be obtained on image quality. In order to obtain the best medical images while minimizing the dose, usage of two upper ion chambers is considered to be clinically useful at sensitivity 625(High).

Introduction of the New Evaluation Criteria in the Forest Sector of Environmental Conservation Value Map Using LiDAR (LiDAR를 활용한 국토환경성평가지도 산림부문 신규 평가항목의 도입 가능성 평가)

  • Jeon, Seong-Woo;Hong, Hyun-Jung;Lee, Chong-Soo;Lee, Woo-Kyun;Sung, Hyun-Chan
    • Journal of the Korean Society of Environmental Restoration Technology
    • /
    • v.10 no.5
    • /
    • pp.20-30
    • /
    • 2007
  • Environmental Conservation Value Assessment Map (ECVAM) is the class map to divide the national land into conservation areas and development areas based on legal and ecological assessment criteria. It contributes to enhancements of the efficiency and the scientificity when framing a policy in various fields including the environment. However, it is impossible to understand the multiphase vegetation structure as data on judging the national forest class in ECVAM are restricted to areal information of Ecological Nature Status, Degree of Green Naturality and Forest Map. This point drops the reliability of ECVAM. Therefore we constructed vegetation information using LiDAR (Light Detection And Raging) technology. We generated Biomass Class Maps as final results of this study, to introduce the new forest assessment criterion in ECVAM that alternates or makes up for existing forest assessment criteria. And then, we compared these with Forest Map and Landsat TM NDVI image. As a result, biomass classes are generally higher than stand age classes and DBH classes of Vegetation Map, and lower than NDVI of Landsat TM image because of the difference of time on data construction. However distributions between these classes are mostly similar. Therefore we estimates that it is possible to apply the biomass item to the new forest assessment criterion of ECVAM. The introduction of the biomass in ECVAM makes it useful to detect the vegetation succession, to adjust the class of the changed zone since the production of Vegetation Map and to rectify the class error of Vegetation Map because variations on tree heights, forest area, gaps between trees, vegetation vitality and so on are acquired as interim findings in process of computing biomass.

Disparity-based Error Concealment for Stereoscopic Images with Superpixel Segmentation

  • Zhang, Yizhang;Tang, Guijin;Liu, Xiaohua;Sun, Changming
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.12 no.9
    • /
    • pp.4375-4388
    • /
    • 2018
  • To solve the problem of transmission errors in stereoscopic images, this paper proposes a novel error concealment (EC) method using superpixel segmentation and adaptive disparity selection (SSADS). Our algorithm consists of two steps. The first step is disparity estimation for each pixel in a reference image. In this step, the numbers of superpixel segmentation labels of stereoscopic images are used as a new constraint for disparity matching to reduce the effect of mismatching. The second step is disparity selection for a lost block. In this step, a strategy based on boundary smoothness is proposed to adaptively select the optimal disparity which is used for error concealment. Experimental results demonstrate that compared with other methods, the proposed method has significant advantages in both objective and subjective quality assessment.

The Effects of Image Dehazing Methods Using Dehazing Contrast-Enhancement Filters on Image Compression

  • Wang, Liping;Zhou, Xiao;Wang, Chengyou;Li, Weizhi
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.10 no.7
    • /
    • pp.3245-3271
    • /
    • 2016
  • To obtain well-dehazed images at the receiver while sustaining low bit rates in the transmission pipeline, this paper investigates the effects of image dehazing methods using dehazing contrast-enhancement filters on image compression for surveillance systems. At first, this paper proposes a novel image dehazing method by using a new method of calculating the transmission function—namely, the direct denoising method. Next, we deduce the dehazing effects of the direct denoising method and image dehazing method based on dark channel prior (DCP) on image compression in terms of ringing artifacts and blocking artifacts. It can be concluded that the direct denoising method performs better than the DCP method for decompressed (reconstructed) images. We also improve the direct denoising method to obtain more desirable dehazed images with higher contrast, using the saliency map as the guidance image to modify the transmission function. Finally, we adjust the parameters of dehazing contrast-enhancement filters to obtain a corresponding composite peak signal-to-noise ratio (CPSNR) and blind image quality assessment (BIQA) of the decompressed images. Experimental results show that different filters have different effects on image compression. Moreover, our proposed dehazing method can strike a balance between image dehazing and image compression.

Digital Image Quality Assessment Based on Standard Normal Deviation

  • Park, Hyung-Ju;Har, Dong-Hwan
    • International Journal of Contents
    • /
    • v.11 no.2
    • /
    • pp.20-30
    • /
    • 2015
  • We propose a new method that specifies objective image quality factors by evaluating an image quality measurement model using random images. In other words, No-Reference variables are used to evaluate the quality of an original image without using any reference for comparison. 1000 portrait images were collected from a web gallery with votes constituting over 30 recommendation values. The bottom-up data collecting process was used to calculate the following image quality factors: total range, average, standard deviation, normalized distribution, z-score, preference percentage. A final grade is awarded out of 100 points, and this method ranks and grades the final estimated image quality preference in terms of total image quality factors. The results of the proposed image quality evaluation model consist of the specific dynamic range, skin tone R, G, B, L, A, B, and RSC contrast. We can present the total for the expected preference points as the average of the objective image qualities. Our proposed image quality evaluation model can measure the preferences for an actual image using a statistical analysis. The results indicate that this is a practical image quality measurement model that can extract a subject's preferred image quality.

Study on the Risk Assessment of Collision Accidents Between Island Bridge and Ship Using an Image Processing Method (영상처리기법을 활용한 연도교와 선박간의 충돌사고 위험성 평가에 관한 연구)

  • Da-Un Jang
    • Journal of the Korean Society of Marine Environment & Safety
    • /
    • v.28 no.7
    • /
    • pp.1111-1119
    • /
    • 2022
  • Tourism projects through islands in the waters of Sinan-gun became active, and as a result, a total of 13 marine bridges connecting islands were completed. However, the marine bridge constructed in the fairway is dangerous for traffic. Particularly, in the case of the marine bridge connecting two islands, the width of the fairway is extremely narrow, therefore the risk is higher. In this study, we evaluated the risk of collision between marine bridge piers and ships using the IALA Waterway Risk Assessment Program (IWRAP), a risk assessment model for port waterways, based on a maritime traffic survey on the coastal bridge in Sinan-gun. The results, indicated that No.1 Sinan bridge had the highest probability of collision and most of the transit ships were coastal passenger ships. In addition, No.1 Sinan bridge was the place where the most collision accidents occurred among the marine bridge piers in the target sea, and the cause this study was analyzed. An analysis of the satellite images of the sea environment of No.1 Sinan bridge using an image processing method, confirmed that obstacles that could not be seen in the chart existed nearby the bridge. As a result, traffic was observed to be concentrated in one direction, unlike two-way traffic, which is a method of inducing traffic of bridges to avoid obstacles. The risk cause analysis method using the image processing technique of this study is expected to be used as a basic research method for analyzing the risk factors of island bridge in the future.