철근의 한계상태변형률 평가를 위한 이미지 프로세싱의 적용

김성도,정치영,우태련,정진환 한국구조물진단유지관리공학회 2016 한국구조물진단유지관리공학회 논문집 Vol.20 No.3

In this study, measurements were conducted by image processing to do an in-depth evaluation of strain of rebar in a uniaxial tension test. The distribution of strain and the necking region were evaluated. The image processing is used to analyze the color information of a colored image, so that the parts consistent with desired targets can be distinguished from the other parts. After this process, the image was converted to a binary one. Centroids of each target region are obtained in the binary images. After repeating such process on the images from starting point to the finishing point of the test, elongation between targets is calculated based on the centroid of each target. The tensile test were conducted on grade 60 #7(D22) and #9(D29) rebars fabricated in accordance with ASTM A615 standards. Strain results from image processing were compared to the results from a conventional strain gauge, in order to see the validity of the image processing. With the image processing, the measuring was possible in not only the initial elastic region but also the necking region of more than 0.5(50%) strain. The image processing can remove the measuring limits as long as the targets can be video recorded. It also can measure strain at various spots because the targets can easily be attached and detached. Thus it is concluded that the image processing helps overcome limits in strain measuring and will be used in various ways. 본 연구에서는 철근의 인장시험에서 변형률에 대한 상세 측정을 위하여 이미지 프로세싱을 이용하고, 변형률 분포와 넥킹구간을 평가하였다. 이미지 프로세싱 방법으로는 기존의 회색조영상을 이용한 방법이 아닌 칼라영상의 색상정보를 분석하여, 원하는 타겟과 가장 일치하는 영역과 그 외의 영역으로 구분하여 이진영상으로 변환하는 방법을 사용하였다. 변환된 이진영상에서 개별 타겟들의 도심점을 산출한 후 각 도심점의 상대변위값을 변형률로 환산하였다. 인장실험은 ASTM A615 기준으로 제작된 grade 60 철근 중 D22와 D29에 대해서 시험을 수행하였다. 이미지 프로세싱을 이용하여 계측된 변형률 결과를 기존 변형률 게이지를 이용하여 계측한 결과와 비교하여, 본 연구에서 사용한 이미지 프로세싱 방법에 대해서 검증하였다. 이미지 프로세싱을 이용하여 초기 탄성구간의 변형률 뿐만 아니라 넥킹구간에서 발생한 0.5 (50%) 이상의 변형률도 계측이 가능한 것을 확인하였다. 본 연구결과 이미지 프로세싱을 통하여 기존 변형률 게이지의 계측한계를 극복가능하고, 다양한 지점에서 자유롭게 계측할 수 있음을 알 수 있었다.

Intracranial CT Angiography에서 3D 영상의 재현성 평가

윤동민(Dong Min Yoon),신상보(Sang Bo Shin),신철경(Sul Kyung Shin),남윤철(Yoon Chul Nam),김문찬(Moon Chan Kim) 대한CT영상기술학회 2012 대한CT영상기술학회지 Vol.14 No.1

목적 두개 내 동맥의 CT검사 후 3D processing을 하는 경우 사용되는 각 장비들을 비교하여 특징을 알아보고 3D processing시 유용한 방법에 대하여 고찰해 보고자 한다. 대상 및 방법 3D processing을 하기 위한 영상을 얻기 위해 Toshiba사의 64 channel MDCT(Aquilion TSX-101A, Toshiba, Japan)를 사용하여 Intracranial artery를 검사한 30명의 영상을 이용하였으며, 동일한 검사 부위의 조영제 주입 전 영상인 non-contrast image(이하 pre image)와 조영제 주입 후 영상인 post contrast image(이하 post image)를 이용하였다. Pre image와 post image를 3D Processing 장비 ADW(GE, version 4.4), Tera-Recon(Aquarius, version 3.7.0.13), Rapidia(Infinitt, version 2.8), Aquilion workstation(Toshiba, version TSX-101A), Intuition(Aquarius, version 4,4)에 각각 전송하고 자체 기능을 이용하여 bone을 제거하여 혈관부위만 남긴 영상을 만들어 ICA(internal carotid artery), BA(basilar artery), ACA(anterior cerebral artery), MCA(middle cerebral artery), PCA(posterior cerebral artery) 부위를 비교하였다. 결과 Rapidia와 Aquilion workstation에서는 CT number값을 이용하여 pre image와 post image를 적용하는 subtraction을 이용하고 있다. Rapidia와 Aquilion workstation에서 bone의 제거가 용이했고 혈관소실이 거의 없었다. Intuition은 display된 pre image와 post image의 pixel을 이용하여 A-B의 형식으로 계산하여 나타내고 이후 auto bone remove기능을 이용하여 혈관과 bone을 구분한다. Intuition은 bone의 제거가 특정부위에서 어려웠고 혈관소실도 있었다. ADW도 display된 pre image와 post image의 pixel을 이용하여 A-B의 형식으로 계산하여 나타내고 이후 auto bone remove기능을 이용하여 혈관과 bone을 구분한다. ADW는 bone의 제거는 용이했지만 특정부위의 혈관소실이 있었다. Tera-recon은 auto bone remove 기능을 이용하여 혈관에서 bone을 제거한다. Tera-recon에서는 bone의 제거가 특정부위에서 어려웠고 혈관소실도 있었다. 결론 CT검사 후 데이터를 이용하여 3D processing을 함에 있어 CT number값을 이용하여 pre image와 post image를 적용하는 subtraction의 기능을 이용하는 Rapidia와 Aquilion workstation의 사용이 보다 유용한 영상을 표현해내며 이는 원본 데이터의 왜곡을 최소화 하고 보다 실제에 가까운 3D 영상을 만든다. I. Purpose When using the 3D processing after the CT scan of intracranial arteries, study of best way to 3D processing and knowing the characteristics of each workstation. II. Material and methods For gain to the 3D image, 30 patients images that underwent CT Angiography, Intracranial Arteries by Toshiba 64 channel MDCT(Aquilion TSX-101A, Toshiba, Japan), images transferred to each 3D processing equipments. Pre and pat image was using the same location, and this images transfer to ADW(GE, version 4.4), Tera-Recon(Aquarius, version 3.7.0.13), Rapidia(Infinitt, version 2.8), Aquilion workstation(Toshiba, version TSX-101A), Intuition(Aquarius, version 4.4). Each workstation makes a 3D artery image without foreign object such as bone, vein, peripheral vessel, it using the self function at that time. Then, conμire the ICA(internal carotid artery), BA(basilar artery), ACA(anterior cerebral artery), MCA(middle cerebral artery), PCA (posterior cerebral artery). III. Result Rapidia and Aquilion workstation was using the CT number, then it takes a subtraction by pre and past image. Rapidia and Aquilion workstation was so useful equipments fee remove the bone and there was little or no loss of vessel. Intuition is using the display pixel of pre and past image, then appear to image such as A-B and compare vessel with bone by auto bone remove function. Intuition is hard to remove the bone and loss of vessel. ADW is also using the display pixel of pre and past image, then appear to image such as A-B and compare vessel with bone by auto bone remove function. ADW is useful equipments for remove the bone but it has loss of vessel. Tera-Recon takes a auto bone remove function and remove the bone from the vessel. Tera-Recon is hard hard to remove the bone and loss of vessel. IV. conclusion When using the 3D processing workstation for 3D image, Rapidia and Aquilion workstation subtraction function that apply to CT number of pre and post image is minimize distortion and so useful to mike a realistic 3D image.

Application of Improved SVM Algorithm in Color Image De-Noising

Dong Tao 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.8

It cannot avoid the noise interference in image processing, whether it is image generation, or image transmission, among them, the most typical noise is salt and pepper noise and Gaussian noise. The salt and pepper noise will cause the image showing the random distribution of noise points, thus greatly reduce the image quality. The Gaussian noise affects the input, collection and output of the image processing. Gaussian noise will make the image blurred. Therefore, the image de-noising plays a very important role in image processing. It has direct influence on image segmentation, feature extraction and image recognition. As is known to all, the support vector machine has the advantages of solving the problem of nonlinear, high dimension and local minimum points. In this article, we use this advantage to propose an image de-noising method which is based on it. The method uses support vector regression to construct the filter for image de-noising. The feature extraction and training samples are designed to suppress different types of noise. Firstly, we use the noise pixel as the center of the 5*5 window, and generate the input vector of SVM from row to column. Secondly, we set the output of the support vector filter as an image that is not contaminated by noise. At this point, we get the training samples of SVM filter. In addition, the parameter selection of support vector machine has a great influence on the result of image de-noising. Therefore, the particle swarm optimization algorithm is proposed in this article to optimize the parameters of SVM. Finally, we adding the simulated salt and pepper noise and Gaussian noise in the original Lena image, and using several methods to carry out the de-noising experiment. From the experimental results we can see that the de-noising effect of filtering algorithm of this paper is very good for the two kinds of noise. It can effectively remove the noise, and better maintain the details and the color of the image.

철근의 한계상태변형률 평가를 위한 이미지 프로세싱의 적용

김상도,정치영,우태련,정진환 한국구조물진단유지관리공학회 2016 한국구조물진단유지관리공학회 논문집 Vol.20 No.3

본 연구에서는 철근의 인장시험에서 변형률에 대한 상세 측정을 위하여 이미지 프로세싱을 이용하고, 변형률 분포와 넥킹구간을 평가하였다. 이미지 프로세싱 방법으로는 기존의 회색조영상을 이용한 방법이 아닌 칼라영상의 색상정보를 분석하여, 원하는 타겟과 가장 일 치하는 영역과 그 외의 영역으로 구분하여 이진영상으로 변환하는 방법을 사용하였다. 변환된 이진영상에서 개별 타겟들의 도심점을 산출한 후 각 도심점의 상대변위값을 변형률로 환산하였다. 인장실험은 ASTM A615 기준으로 제작된 grade 60 철근 중 D22와 D29에 대해서 시험을 수행하였다. 이미지 프로세싱을 이용하여 계측된 변형률 결과를 기존 변형률 게이지를 이용하여 계측한 결과와 비교하여, 본 연구에서 사용한 이미지 프로세싱 방법에 대해서 검증하였다. 이미지 프로세싱을 이용하여 초기 탄성구간의 변형률 뿐만 아니라 넥킹구간에서 발생한 0.5 (50%) 이상의 변형률도 계측이 가능한 것을 확인하였다. 본 연구결과 이미지 프로세싱을 통하여 기존 변형률 게이지의 계측한계를 극복가능 하고, 다양한 지점에서 자유롭게 계측할 수 있음을 알 수 있었다. In this study, measurements were conducted by image processing to do an in-depth evaluation of strain of rebar in a uniaxial tension test. The distribution of strain and the necking region were evaluated. The image processing is used to analyze the color information of a colored image, so that the parts consistent with desired targets can be distinguished from the other parts. After this process, the image was converted to a binary one. Centroids of each target region are obtained in the binary images. After repeating such process on the images from starting point to the finishing point of the test, elongation between targets is calculated based on the centroid of each target. The tensile test were conducted on grade 60 #7(D22) and #9(D29) rebars fabricated in accordance with ASTM A615 standards. Strain results from image processing were compared to the results from a conventional strain gauge, in order to see the validity of the image processing. With the image processing, the measuring was possible in not only the initial elastic region but also the necking region of more than 0.5(50%) strain. The image processing can remove the measuring limits as long as the targets can be video recorded. It also can measure strain at various spots because the targets can easily be attached and detached. Thus it is concluded that the image processing helps overcome limits in strain measuring and will be used in various ways.

A Review on Modified Image Enhancement Applications

Mahendra PS Kuber,Manish Dixit 보안공학연구지원센터 2014 International Journal of Signal Processing, Image Vol.7 No.5

The aim of image enhancement is to or to provide ‘better’ input for other improve the interpretability or perception of information in images for human viewing automated image processing techniques. Various Histogram Equalization techniques like CHE, GHE, BBHE, DSIHE, RMSHE and Multi-HE techniques are used for processing the image input to enhance its output. This paper provides a review over the modification of the brightness preserving dynamic histogram equalization technique to improve its brightness preserving and contrast enhancement abilities while reducing its computational complexity. There are many modified technique related to brightness preserving dynamic Histogram Equalization that uses statistics of digital images for their representation and processing are discussed here. Representation and processing of images in the spatial domain enables the technique to handle the inexactness of gray level values in a better way, resulting in improved performance. This algorithm enhances image contrast as well as preserves the brightness very effectively. Some images are not available to good quality, so these algorithms are used for image enhancement to improve the quality of the image.

Application of Webcam for Inspection of Rice Grain Quality by Using Image Processing Technique

Witsarut Sriratana,Namo Narknam,Ruangsit Apichitanon,Narin Tammarugwattana 제어로봇시스템학회 2020 제어로봇시스템학회 국제학술대회 논문집 Vol.2020 No.10

This paper presents the image processing system for quality inspection of rice grains after sorting process by using an ordinary webcam to ensure that rice grains should meet the quality standards and impurity such as grits, dirt and stones should not be found [1]. Moreover, statistical information of rice grains from image processing could be taken into analysis to enhance the efficiency of the sorting process. Image data analysis of rice grains can be divided into 2 main arrangement conditions, non-overlapping and overlapping. In this study, the experiments to inspect rice grains were applied for 24 samples and 18 experimental designs including the complete and incomplete structures, the overlapping and non-overlapping arrangements, and the combination of rice grains from complete and incomplete structures in equal and unequal ratios. From experiments, it was found that the inspection of rice grain quality by using image processing technique and image data recorded by an ordinary webcam was reliable and efficient. The inspection errors under non-overlapping arrangement condition of complete and incomplete structures of rice grains were not observed. The inspection errors of rice grains combined from complete and incomplete structures in equal and unequal ratios were about 0.8% and 1.11%, respectively. However, under overlapping arrangement condition, it was observed that the inspection errors of image processing would be high by up to 53.82% on average.

고해상도 이미지 처리를 위한 PIM 기반 JPEG 디코더 병렬화 기법 구현

김지은,남덕윤 한국통신학회 2025 한국통신학회논문지 Vol.50 No.2

JPEG은 이미지 크기를 효과적으로 줄일 수 있어 다양한 응용 분야에서 널리 사용되는 디지털 이미지 형식이다. JPEG 디코딩은 압축된 이미지 데이터를 복원하여 디스플레이하거나 후처리하기 위해 필요한 과정으로, 실시간 애플리케이션과 딥러닝과 같은 대량 이미지 처리 분야에서 중요한 역할을 한다. 그러나 JPEG 디코딩은 성능의병목 지점이 될 수 있어, 이를 극복하기 위한 다양한 가속기 기반 병렬 처리 기법들이 제안되었다. 최근에는Processing-in-Memory (PIM) 아키텍처를 활용한 연구들이 주목받고 있으며, 기존 연구인 PIM 기반 JPEG 디코더는 하드웨어 스레드와 AAN 알고리즘을 적용하여 성능 개선을 도모하였으나, DPU당 제한된 메모리 용량 및DPU 간 통신 부재로 처리 가능한 이미지 해상도에 한계가 있었다. 본 연구에서는 JPEG 디코딩 파이프라인을 수정하여 이러한 한계를 극복하는 방안을 제안한다. 허프만 디코딩을 호스트 CPU에서 수행함으로써 DPU 간 통신의 필요성을 없애고, MCU (Minimum Coded Unit) 간 데이터 의존성 없이 병렬 처리가 가능하도록 설계하였다. UPMEM PIM 서버에서 고해상도 이미지 데이터 세트를 사용하여 실험을 수행한 결과, 본 연구에서 구현한 디코더는 기존 PIM 디코더가 처리할 수 없었던 고해상도 이미지를 디코딩할 수 있음을 확인할 수 있었다. JPEG is a digital image format widely used in various applications due to its ability to effectively reduce image file size. JPEG decoding involves restoring compressed image data for display or post-processing and plays a crucial role in fields such as real-time applications and deep learning, where large-scale image processing is required. However, JPEG decoding can become a performance bottleneck, prompting the development of various accelerator-based parallel processing techniques. Recently, research utilizing Processing-in-Memory (PIM) architectures has gained attention. Existing studies on PIM-based JPEG decoders have applied hardware threads and the AAN algorithm to improve performance, but limitations such as constrained memory capacity per DPU and lack of inter-DPU communication have restricted the resolution of image that can be processed. In this paper, we propose a modified JPEG decoding pipeline to overcome these limitations. By performing Huffman decoding in the host CPU, the need for inter-DPU communication is eliminated, enabling parallel processing without data dependencies between MCUs (Minimum Coded Units). Experiments conducted on the UPMEM PIM server using a high-resolution image dataset show that the proposed decoder can successfully decode high-resolution images that the existing PIM decoder could not process.

Dynamic Memory Access Control for Accelerating FPGA-based Image Processing

Kenta Nishiguchi,Toshiyuki Inoue,Rei Yamazaki,Kazunori Ogohara,Akira Tsuchiya,Keiji Kishine 대한전자공학회 2021 Journal of semiconductor technology and science Vol.21 No.1

In an FPGA-based image processing system, memory access plays an important role in increasing the speed of image processing. With the conventional method, the memory access interval for image processing was fixed, which limited the processing speed. In this work, we developed a novel memory access method that dynamically controls the intervals between memory access requests for image processing by monitoring the memory status. We implemented an image processing system with the proposed method and examined its characteristics. The maximum processing speed with the proposed method reached 30.7 fps, which was 1.65 times faster than that of the conventional method.

콜라주 기법을 활용한 개인의 시각이미지 처리 과정에 관한 연구

이소민,이혜선 한국기초조형학회 2025 기초조형학연구 Vol.26 No.2

This study explored consumers' personal visual image processing tastes using collage, an image-based research methodology. Seventeen female Generation Z design students participated in collage creation, with seven selected for follow-up interviews to analyze their image expression methods and approaches. The analysis revealed that collage image expression could be categorized into 'content aspects (implicit/fragmentary meaning)' and 'relational aspects (holistic/individual composition)'. Based on this categorization, participants were divided into a group with 'fragmentary meaning-individual composition' and a group with 'implicit meaning-holistic composition'. The former expressed fragmentary meanings related to the external characteristics of preferred objects, focusing on individual image features, while the latter conveyed implicit meanings through symbolic images of one's inner self, emphasizing overall composition and harmony. Furthermore, participants were classified according to their image selection process into 'bottom-up' (selecting individual images first, then forming the whole) and 'top-down' (setting a theme first, then selecting images accordingly) approaches. 'Bottom-up' participants focused on the uniqueness and details of images, while 'top-down' participants prioritized overall harmony and balance. This study is meaningful in that it conducted an in-depth analysis and categorization of the diverse factors influencing individuals' image preferences and visual image processing, through the process of creating collages with self-selected images. This highlights the usefulness of collage as a qualitative research method for effectively understanding evolving consumer preferences. Given the limited application of collage in design research and the scarcity of studies analyzing collage outcomes, this study contributes academically by introducing a novel approach that broadens methodological diversity in design research and validates the potential of image-based research. However, a limitation of this study is the small sample size, inherent to qualitative research. Future studies should consider image analysis methods based on online platforms employing image analysis techniques based on online platforms to broaden the scope of research and enhance diversity.

Off-Site Distortion and Color Compensation of Underwater Archaeological Images Photographed in the Very Turbid Yellow Sea

Young-Hwa Jung,Gyuho Kim,Woo Sik Yoo 한국문화재보존과학회 2022 보존과학회지 Vol.38 No.1

Underwater photographing and image recording are essential for pre-excavation survey and during excavation in underwater archaeology. Unlike photographing on land, all underwater images suffer various quality degradations such as shape distortions, color shift, blur, low contrast, high noise levels and so on. Outcome is very often heavily photographing equipment and photographer dependent. Excavation schedule, weather conditions, and water conditions can put burdens on divers. Usable images are very limited compared to the efforts. In underwater archaeological study in very turbid water such as in the Yellow Sea (between mainland China and the Korean peninsula), underwater photographing is very challenging. In this study, off-site image distortion and color compensation techniques using an image processing/analysis software is investigated as an alternative image quality enhancement method. As sample images, photographs taken during the excavation of 800-year-old Taean Mado Shipwrecks in the Yellow Sea in 2008-2010 were mainly used. Significant enhancement in distortion and color compensation of archived images were obtained by simple post image processing using image processing/analysis software (PicMan) customized for given view ports, lenses and cameras with and without optical axis offsets. Post image processing is found to be very effective in distortion and color compensation of both recent and archived images from various photographing equipment models and configurations. Merits and demerit of in-situ, distortion and color compensated photographing with sophisticated equipment and conventional photographing equipment, which requires post image processing, are compared.