• Title/Summary/Keyword: Light field image

Search Result 266, Processing Time 0.023 seconds

Design of Two Layer Depth-encoding Detector Module with SiPM for PET (SiPM을 사용한 두 층의 반응 깊이를 측정하는 양전자방출단층촬영기기의 검출기 모듈 설계)

  • Lee, Seung-Jae
    • Journal of the Korean Society of Radiology
    • /
    • v.13 no.3
    • /
    • pp.319-324
    • /
    • 2019
  • A depth-encoding detector module with silicon photomultipliers(SiPMs) using two layers of scintillation crystal array was designed, and the position measurement capability was verified using DETECT2000. The depth of interaction of the crystal pixels with the gamma rays was tracked through the image acquired with the combination of surface treatment of the crystal pixels and reflectors. The bottom layer was treated as a reflector except for the optically coupled surfaces, and the crystals of top layer were optically coupled each other except for the outer surfaces so that the light sharing was made easier than the bottom layer. Flood images were obtained through the combination of specular reflectors and random reflectors, grounded and polished surfaces of crystal pixels, and the positions at which layer images were generated were measured and analyzed. The images were reconstructed using the Anger algorithm, whose the SiPM signals were reduced as the 16-channels to 4-channels. In the combination of the grounded surface and all reflectors, the depth positions were discriminated into two layers, whereas it was impossible to separate the two layers in the all polished surface combinations. Therefore, using the combination of grounded surface crystal pixels and reflectors could improve the spatial resolution at the outside of the field of view by measuring the depth position in preclinical positron emission tomography.

D4AR - A 4-DIMENSIONAL AUGMENTED REALITY - MODEL FOR AUTOMATION AND VISUALIZATION OF CONSTRUCTION PROGRESS MONITORING

  • Mani Golparvar-Fard;Feniosky Pena-Mora
    • International conference on construction engineering and project management
    • /
    • 2009.05a
    • /
    • pp.30-31
    • /
    • 2009
  • Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.

  • PDF

System Development for Measuring Group Engagement in the Art Center (공연장에서 다중 몰입도 측정을 위한 시스템 개발)

  • Ryu, Joon Mo;Choi, Il Young;Choi, Lee Kwon;Kim, Jae Kyeong
    • Journal of Intelligence and Information Systems
    • /
    • v.20 no.3
    • /
    • pp.45-58
    • /
    • 2014
  • The Korean Culture Contents spread out to Worldwide, because the Korean wave is sweeping in the world. The contents stand in the middle of the Korean wave that we are used it. Each country is ongoing to keep their Culture industry improve the national brand and High added value. Performing contents is important factor of arousal in the enterprise industry. To improve high arousal confidence of product and positive attitude by populace is one of important factor by advertiser. Culture contents is the same situation. If culture contents have trusted by everyone, they will give information their around to spread word-of-mouth. So, many researcher study to measure for person's arousal analysis by statistical survey, physiological response, body movement and facial expression. First, Statistical survey has a problem that it is not possible to measure each person's arousal real time and we cannot get good survey result after they watched contents. Second, physiological response should be checked with surround because experimenter sets sensors up their chair or space by each of them. Additionally it is difficult to handle provided amount of information with real time from their sensor. Third, body movement is easy to get their movement from camera but it difficult to set up experimental condition, to measure their body language and to get the meaning. Lastly, many researcher study facial expression. They measures facial expression, eye tracking and face posed. Most of previous studies about arousal and interest are mostly limited to reaction of just one person and they have problems with application multi audiences. They have a particular method, for example they need room light surround, but set limits only one person and special environment condition in the laboratory. Also, we need to measure arousal in the contents, but is difficult to define also it is not easy to collect reaction by audiences immediately. Many audience in the theater watch performance. We suggest the system to measure multi-audience's reaction with real-time during performance. We use difference image analysis method for multi-audience but it weaks a dark field. To overcome dark environment during recoding IR camera can get the photo from dark area. In addition we present Multi-Audience Engagement Index (MAEI) to calculate algorithm which sources from sound, audience' movement and eye tracking value. Algorithm calculates audience arousal from the mobile survey, sound value, audience' reaction and audience eye's tracking. It improves accuracy of Multi-Audience Engagement Index, we compare Multi-Audience Engagement Index with mobile survey. And then it send the result to reporting system and proposal an interested persons. Mobile surveys are easy, fast, and visitors' discomfort can be minimized. Also additional information can be provided mobile advantage. Mobile application to communicate with the database, real-time information on visitors' attitudes focused on the content stored. Database can provide different survey every time based on provided information. The example shown in the survey are as follows: Impressive scene, Satisfied, Touched, Interested, Didn't pay attention and so on. The suggested system is combine as 3 parts. The system consist of three parts, External Device, Server and Internal Device. External Device can record multi-Audience in the dark field with IR camera and sound signal. Also we use survey with mobile application and send the data to ERD Server DB. The Server part's contain contents' data, such as each scene's weights value, group audience weights index, camera control program, algorithm and calculate Multi-Audience Engagement Index. Internal Device presents Multi-Audience Engagement Index with Web UI, print and display field monitor. Our system is test-operated by the Mogencelab in the DMC display exhibition hall which is located in the Sangam Dong, Mapo Gu, Seoul. We have still gotten from visitor daily. If we find this system audience arousal factor with this will be very useful to create contents.

Quantitative Analysis of Digital Radiography Pixel Values to absorbed Energy of Detector based on the X-Ray Energy Spectrum Model (X선 스펙트럼 모델을 이용한 DR 화소값과 디텍터 흡수에너지의 관계에 대한 정량적 분석)

  • Kim Do-Il;Kim Sung-Hyun;Ho Dong-Su;Choe Bo-young;Suh Tae-Suk;Lee Jae-Mun;Lee Hyoung-Koo
    • Progress in Medical Physics
    • /
    • v.15 no.4
    • /
    • pp.202-209
    • /
    • 2004
  • Flat panel based digital radiography (DR) systems have recently become useful and important in the field of diagnostic radiology. For DRs with amorphous silicon photosensors, CsI(TI) is normally used as the scintillator, which produces visible light corresponding to the absorbed radiation energy. The visible light photons are converted into electric signal in the amorphous silicon photodiodes which constitute a two dimensional array. In order to produce good quality images, detailed behaviors of DR detectors to radiation must be studied. The relationship between air exposure and the DR outputs has been investigated in many studies. But this relationship was investigated under the condition of the fixed tube voltage. In this study, we investigated the relationship between the DR outputs and X-ray in terms of the absorbed energy in the detector rather than the air exposure using SPEC-l8, an X-ray energy spectrum model. Measured exposure was compared with calculated exposure for obtaining the inherent filtration that is a important input variable of SPEC-l8. The absorbed energy in the detector was calculated using algorithm of calculating the absorbed energy in the material and pixel values of real images under various conditions was obtained. The characteristic curve was obtained using the relationship of two parameter and the results were verified using phantoms made of water and aluminum. The pixel values of the phantom image were estimated and compared with the characteristic curve under various conditions. It was found that the relationship between the DR outputs and the absorbed energy in the detector was almost linear. In a experiment using the phantoms, the estimated pixel values agreed with the characteristic curve, although the effect of scattered photons introduced some errors. However, effect of a scattered X-ray must be studied because it was not included in the calculation algorithm. The result of this study can provide useful information about a pre-processing of digital radiography.

  • PDF

Development of Geometrical Quality Control Real-time Analysis Program using an Electronic Portal Imaging (전자포탈영상을 이용한 기하학적 정도관리 실시간 분석 프로그램의 개발)

  • Lee, Sang-Rok;Jung, Kyung-Yong;Jang, Min-Sun;Lee, Byung-Gu;Kwon, Young-Ho
    • The Journal of Korean Society for Radiation Therapy
    • /
    • v.24 no.2
    • /
    • pp.77-84
    • /
    • 2012
  • Purpose: To develop a geometrical quality control real-time analysis program using an electronic portal imaging to replace film evaluation method. Materials and Methods: A geometrical quality control item was established with the Eclipse treatment planning system (Version 8.1, Varian, USA) after the Electronic Portal Imaging Device (EPID) took care of the problems occurring from the fixed substructure of the linear accelerator (CL-iX, Varian, USA). Electronic portal image (single exposure before plan) was created at the treatment room's 4DTC (Version 10.2, Varian, USA) and a beam was irradiated in accordance with each item. The gaining the entire electronic portal imaging at the Off-line review and was evaluated by a self-developed geometrical quality control real-time analysis program. As for evaluation methods, the intra-fraction error was analyzed by executing 5 times in a row under identical conditions and procedures on the same day, and in order to confirm the infer-fraction error, it was executed for 10 days under identical conditions of all procedures and was compared with the film evaluation method using an Iso-align$^{TM}$ quality control device. Measurement and analysis time was measured by sorting the time into from the device setup to data achievement and the time amount after the time until the completion of analysis and the convenience of the users and execution processes were compared. Results: The intra-fraction error values for each average 0.1, 0.2, 0.3, 0.2 mm at light-radiation field coincidence, collimator rotation axis, couch rotation axis and gantry rotation axis. By checking the infer-fraction error through 10 days of continuous quality control, the error values obtained were average 1.7, 1.4, 0.7, 1.1 mm for each item. Also, the measurement times were average 36 minutes, 15 minutes for the film evaluation method and electronic portal imaging system, and the analysis times were average 30 minutes, 22 minutes. Conclusion: When conducting a geometrical quality control using an electronic portal imaging, it was found that it is efficient as a quality control tool. It not only reduces costs through not using films, but also reduces the measurement and analysis time which enhances user convenience and can improve the execution process by leaving out film developing procedures etc. Also, images done with evaluation from the self-developed geometrical quality control real-time analysis program, data processing is capable which supports the storage of information.

  • PDF

Color Analyses on Digital Photos Using Machine Learning and KSCA - Focusing on Korean Natural Daytime/nighttime Scenery - (머신러닝과 KSCA를 활용한 디지털 사진의 색 분석 -한국 자연 풍경 낮과 밤 사진을 중심으로-)

  • Gwon, Huieun;KOO, Ja Joon
    • Trans-
    • /
    • v.12
    • /
    • pp.51-79
    • /
    • 2022
  • This study investigates the methods for deriving colors which can serve as a reference to users such as designers and or contents creators who search for online images from the web portal sites using specific words for color planning and more. Two experiments were conducted in order to accomplish this. Digital scenery photos within the geographic scope of Korea were downloaded from web portal sites, and those photos were studied to find out what colors were used to describe daytime and nighttime. Machine learning was used as the study methodology to classify colors in daytime and nighttime, and KSCA was used to derive the color frequency of daytime and nighttime photos and to compare and analyze the two results. The results of classifying the colors of daytime and nighttime photos using machine learning show that, when classifying the colors by 51~100%, the area of daytime colors was approximately 2.45 times greater than that of nighttime colors. The colors of the daytime class were distributed by brightness with white as its center, while that of the nighttime class was distributed with black as its center. Colors that accounted for over 70% of the daytime class were 647, those over 70% of the nighttime class were 252, and the rest (31-69%) were 101. The number of colors in the middle area was low, while other colors were classified relatively clearly into day and night. The resulting color distributions in the daytime and nighttime classes were able to provide the borderline color values of the two classes that are classified by brightness. As a result of analyzing the frequency of digital photos using KSCA, colors around yellow were expressed in generally bright daytime photos, while colors around blue value were expressed in dark night photos. For frequency of daytime photos, colors on the upper 40% had low chroma, almost being achromatic. Also, colors that are close to white and black showed the highest frequency, indicating a large difference in brightness. Meanwhile, for colors with frequency from top 5 to 10, yellow green was expressed darkly, and navy blue was expressed brightly, partially composing a complex harmony. When examining the color band, various colors, brightness, and chroma including light blue, achromatic colors, and warm colors were shown, failing to compose a generally harmonious arrangement of colors. For the frequency of nighttime photos, colors in approximately the upper 50% are dark colors with a brightness value of 2 (Munsell signal). In comparison, the brightness of middle frequency (50-80%) is relatively higher (brightness values of 3-4), and the brightness difference of various colors was large in the lower 20%. Colors that are not cool colors could be found intermittently in the lower 8% of frequency. When examining the color band, there was a general harmonious arrangement of colors centered on navy blue. As the results of conducting the experiment using two methods in this study, machine learning could classify colors into two or more classes, and could evaluate how close an image was with certain colors to a certain class. This method cannot be used if an image cannot be classified into a certain class. The result of such color distribution would serve as a reference when determining how close a certain color is to one of the two classes when the color is used as a dominant color in the base or background color of a certain design. Also, when dividing the analyzed images into several classes, even colors that have not been used in the analyzed image can be determined to find out how close they are to a certain class according to the color distribution properties of each class. Nevertheless, the results cannot be used to find out whether a specific color was used in the class and by how much it was used. To investigate such an issue, frequency analysis was conducted using KSCA. The color frequency could be measured within the range of images used in the experiment. The resulting values of color distribution and frequency from this study would serve as references for color planning of digital design regarding natural scenery in the geographic scope of Korea. Also, the two experiments are meaningful attempts for searching the methods for deriving colors that can be a useful reference among numerous images for content creator users of the relevant field.