• Title/Summary/Keyword: Real Time Image Processing

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Development of the Algofithm for Gaussian Mixture Models based Traffic Accident Auto-Detection in Freeway (GMM(Gaussian Mixture Model)을 적용한 영상처리기법의 연속류도로 사고 자동검지 알고리즘 개발)

  • O, Ju-Taek;Im, Jae-Geuk;Yeo, Tae-Dong
    • Journal of Korean Society of Transportation
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    • v.28 no.3
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    • pp.169-183
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    • 2010
  • Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a freeway and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, existing technologies, this freeway attribute, velocity changes, volume changes, occupancy changes reflect judge the primary. Furthermore, We pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian Mixture model analytical method which has been considered the best among well-known environmental obstacle reduction methods. Therefore, in this way, the accident was the final decision. Also, environmental factors occur frequently, and with the index finger situations, effectively reducing that can actively and environmentally adaptive techniques through accident final judgment. This implementation of the evaluate performance of the experiment road of 12 incidents in simulated and the jang-hang IC's real-time accident experiment. As a result, the do well detection 93.33%, false alarm 6.7% as showed high reliability.

A Study on Treatment Target Position Verification by using Electronic Portal Imaging Device & Fractionated Stereotatic Radiotherapy (EPID와 FSRT를 이용한 치료표적위치 검증에 관한 연구)

  • Lee, Dong-Hoon;Kwon, Jang-Woo;Park, Seung-Woo;Kim, Yoon-Jong;Lee, Dong-Han;Ji, Young-Hoon
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.46 no.3
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    • pp.44-51
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    • 2009
  • It is very important to verify generated setup errors in cancer therapy by using a high energy radiation and to perform the precise radiation therapy. Specially, the verification of treatment position is very crucial in special therapies like fractionated stereotatic radiotherapy (FSRT). The FSRT uses normally high-dose, small field size for treating small intracranial lesions. To estimate the developed FSRT system, the isocenter accuracy of gantry, couch and collimator were performed and a total of inaccuracy was less than ${\pm}1mm$. Precise beam targeting is crucial when using high-dose, small field size FSRT for treating small intracranial lesions. The EPID image of the 3mm lead ball mounted on the isocenter with a 25mm collimator cone was acquired and detected to the extent of one pixel (0.76mm) after comparing the difference between the center of a 25mm collimator cone and a 3 mm ball after processing the EPID image. In this paper, the radiation treatment efficiency can be improved by performing precise radiation therapy with a developed video based EPID and FSRT at near real time

A Pipelined Parallel Optimized Design for Convolution-based Non-Cascaded Architecture of JPEG2000 DWT (JPEG2000 이산웨이블릿변환의 컨볼루션기반 non-cascaded 아키텍처를 위한 pipelined parallel 최적화 설계)

  • Lee, Seung-Kwon;Kong, Jin-Hyeung
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.46 no.7
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    • pp.29-38
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    • 2009
  • In this paper, a high performance pipelined computing design of parallel multiplier-temporal buffer-parallel accumulator is present for the convolution-based non-cascaded architecture aiming at the real time Discrete Wavelet Transform(DWT) processing. The convolved multiplication of DWT would be reduced upto 1/4 by utilizing the filter coefficients symmetry and the up/down sampling; and it could be dealt with 3-5 times faster computation by LUT-based DA multiplication of multiple filter coefficients parallelized for product terms with an image data. Further, the reutilization of computed product terms could be achieved by storing in the temporal buffer, which yields the saving of computation as well as dynamic power by 50%. The convolved product terms of image data and filter coefficients are realigned and stored in the temporal buffer for the accumulated addition. Then, the buffer management of parallel aligned storage is carried out for the high speed sequential retrieval of parallel accumulations. The convolved computation is pipelined with parallel multiplier-temporal buffer-parallel accumulation in which the parallelization of temporal buffer and accumulator is optimize, with respect to the performance of parallel DA multiplier, to improve the pipelining performance. The proposed architecture is back-end designed with 0.18um library, which verifies the 30fps throughput of SVGA(800$\times$600) images at 90MHz.

Identification of Japanese Black Cattle by the Faces for Precision Livestock Farming (흑소의 얼굴을 이용한 개체인식)

  • 김현태;지전선랑;서률귀구;이인복
    • Journal of Biosystems Engineering
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    • v.29 no.4
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    • pp.341-346
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    • 2004
  • Recent livestock people concern not only increase of production, but also superior quality of animal-breeding environment. So far, the optimization of the breeding and air environment has been focused on the production increase. In the very near future, the optimization will be emphasized on the environment for the animal welfare and health. Especially, cattle farming demands the precision livestock farming and special attention has to be given to the management of feeding, animal health and fertility. The management of individual animal is the first step for precision livestock farming and animal welfare, and recognizing each individual is important for that. Though electronic identification of a cattle such as RFID(Radio Frequency Identification) has many advantages, RFID implementations practically involve several problems such as the reading speed and distance. In that sense, computer vision might be more effective than RFID for the identification of an individual animal. The researches on the identification of cattle via image processing were mostly performed with the cows having black-white patterns of the Holstein. But, the native Korean and Japanese cattle do not have any definite pattern on the body. The purpose of this research is to identify the Japanese black cattle that does not have a body pattern using computer vision technology and neural network algorithm. Twelve heads of Japanese black cattle have been tested to verify the proposed scheme. The values of input parameters were specified and then computed using the face images of cattle. The images of cattle faces were trained using associate neural network algorithm, and the algorithm was verified by the face images that were transformed using brightness, distortion, and noise factors. As a result, there was difference due to transform ratio of the brightness, distortion, and noise. And, the proposed algorithm could identify 100% in the range from -3 to +3 degrees of the brightness, from -2 to +4 degrees of the distortion, and from 0% to 60% of the noise transformed images. It is concluded that our system can not be applied in real time recognition of the moving cows, but can be used for the cattle being at a standstill.

Verification of GEO-KOMPSAT-2A AMI Radiometric Calibration Parameters Using an Evaluation Tool (분석툴을 이용한 천리안2A 기상탑재체 복사 보정 파라미터 검증)

  • Jin, Kyoungwook;Park, Jin-Hyung
    • Korean Journal of Remote Sensing
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    • v.36 no.6_1
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    • pp.1323-1337
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    • 2020
  • GEO-KOMPSAT-2A AMI (Advanced Meteorological Imager) radiometric calibration evaluation is an essential element not only for functional and performance verification of the payload but for the quality of the sensor data. AMI instrument consists of six reflective channels and ten thermal infrared ones. One of the key parameters representing radiometric properties of the sensor is a SNR (Signal-to-Noise Ratio) for the reflective channels and a NEdT (Noise Equivalent delta Temperature) for the IR ones respectively. Other important radiometric calibration parameters are a dynamic range and a gain value related with the responsivity of detectors. To verify major radiometric calibration performance of AMI, an offline radiometric evaluation tool was developed separately with a real-time AMI data processing system. Using the evaluation tool, validation activities were carried out during the GEO-KOMPSAT-2A In-Orbit Test period. The results from the evaluation tool were cross checked with those of the HARRIS, which is the AMI payload vendor. AMI radiometric evaluation activities were conducted through three phases for both sides (Side 1 and Side 2) of AMI payload. Results showed that performances of the key radiometric properties were outstanding with respect to the radiometric requirements of the payload. The effectiveness of the evaluation tool was verified as well.

A Study on the AI Analysis of Crop Area Data in Aquaponics (아쿠아포닉스 환경에서의 작물 면적 데이터 AI 분석 연구)

  • Eun-Young Choi;Hyoun-Sup Lee;Joo Hyoung Cha;Lim-Gun Lee
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.3
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    • pp.861-866
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    • 2023
  • Unlike conventional smart farms that require chemical fertilizers and large spaces, aquaponics farming, which utilizes the symbiotic relationship between aquatic organisms and crops to grow crops even in abnormal environments such as environmental pollution and climate change, is being actively researched. Different crops require different environments and nutrients for growth, so it is necessary to configure the ratio of aquatic organisms optimized for crop growth. This study proposes a method to measure the degree of growth based on area and volume using image processing techniques in an aquaponics environment. Tilapia, carp, catfish, and lettuce crops, which are aquatic organisms that produce organic matter through excrement, were tested in an aquaponics environment. Through 2D and 3D image analysis of lettuce and real-time data analysis, the growth degree was evaluated using the area and volume information of lettuce. The results of the experiment proved that it is possible to manage cultivation by utilizing the area and volume information of lettuce. It is expected that it will be possible to provide production prediction services to farmers by utilizing aquatic life and growth information. It will also be a starting point for solving problems in the changing agricultural environment.

A Framework of Recognition and Tracking for Underwater Objects based on Sonar Images : Part 2. Design and Implementation of Realtime Framework using Probabilistic Candidate Selection (소나 영상 기반의 수중 물체 인식과 추종을 위한 구조 : Part 2. 확률적 후보 선택을 통한 실시간 프레임워크의 설계 및 구현)

  • Lee, Yeongjun;Kim, Tae Gyun;Lee, Jihong;Choi, Hyun-Taek
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.3
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    • pp.164-173
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    • 2014
  • In underwater robotics, vision would be a key element for recognition in underwater environments. However, due to turbidity an underwater optical camera is rarely available. An underwater imaging sonar, as an alternative, delivers low quality sonar images which are not stable and accurate enough to find out natural objects by image processing. For this, artificial landmarks based on the characteristics of ultrasonic waves and their recognition method by a shape matrix transformation were proposed and were proven in Part 1. But, this is not working properly in undulating and dynamically noisy sea-bottom. To solve this, we propose a framework providing a selection phase of likelihood candidates, a selection phase for final candidates, recognition phase and tracking phase in sequence images, where a particle filter based selection mechanism to eliminate fake candidates and a mean shift based tracking algorithm are also proposed. All 4 steps are running in parallel and real-time processing. The proposed framework is flexible to add and to modify internal algorithms. A pool test and sea trial are carried out to prove the performance, and detail analysis of experimental results are done. Information is obtained from tracking phase such as relative distance, bearing will be expected to be used for control and navigation of underwater robots.

A Strategy To Reduce Network Traffic Using Two-layered Cache Servers for Continuous Media Data on the Wide Area Network (이중 캐쉬 서버를 사용한 실시간 데이터의 좡대역 네트워크 대역폭 감소 정책)

  • Park, Yong-Woon;Beak, Kun-Hyo;Chung, Ki-Dong
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.10
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    • pp.3262-3271
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    • 2000
  • Continuous media objects, due to large volume and real-time consiraints in their delivery,are likely to consume much network andwidth Generally, proxy servers are used to hold the fiequently requested objects so as to reduce the network traffic to the central server but most of them are designed for text and image dae that they do not go well with continuous media data. So, in this paper, we propose a two-layered network cache management policy for continuous media object delivery on the wide area networks. With the proposed cache management scheme,in cach LAN, there exists one LAN cache and each LAN is further devided into a group of sub-LANs, each of which also has its own sub-LAN eache. Further, each object is also partitioned into two parts the front-end and rear-end partition. they can be loaded in the same cache or separately in different network caches according to their access frequencics. By doing so, cache replacement overhead could be educed as compared to the case of the full size daa allocation and replacement , this eventually reduces the backbone network traffic to the origin server.

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Liver Splitting Using 2 Points for Liver Graft Volumetry (간 이식편의 체적 예측을 위한 2점 이용 간 분리)

  • Seo, Jeong-Joo;Park, Jong-Won
    • The KIPS Transactions:PartB
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    • v.19B no.2
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    • pp.123-126
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    • 2012
  • This paper proposed a method to separate a liver into left and right liver lobes for simple and exact volumetry of the river graft at abdominal MDCT(Multi-Detector Computed Tomography) image before the living donor liver transplantation. A medical team can evaluate an accurate river graft with minimized interaction between the team and a system using this algorithm for ensuring donor's and recipient's safe. On the image of segmented liver, 2 points(PMHV: a point in Middle Hepatic Vein and PPV: a point at the beginning of right branch of Portal Vein) are selected to separate a liver into left and right liver lobes. Middle hepatic vein is automatically segmented using PMHV, and the cutting line is decided on the basis of segmented Middle Hepatic Vein. A liver is separated on connecting the cutting line and PPV. The volume and ratio of the river graft are estimated. The volume estimated using 2 points are compared with a manual volume that diagnostic radiologist processed and estimated and the weight measured during surgery to support proof of exact volume. The mean ${\pm}$ standard deviation of the differences between the actual weights and the estimated volumes was $162.38cm^3{\pm}124.39$ in the case of manual segmentation and $107.69cm^3{\pm}97.24$ in the case of 2 points method. The correlation coefficient between the actual weight and the manually estimated volume is 0.79, and the correlation coefficient between the actual weight and the volume estimated using 2 points is 0.87. After selection the 2 points, the time involved in separation a liver into left and right river lobe and volumetry of them is measured for confirmation that the algorithm can be used on real time during surgery. The mean ${\pm}$ standard deviation of the process time is $57.28sec{\pm}32.81$ per 1 data set ($149.17pages{\pm}55.92$).

A Study of the Reactive Movement Synchronization for Analysis of Group Flow (그룹 몰입도 판단을 위한 움직임 동기화 연구)

  • Ryu, Joon Mo;Park, Seung-Bo;Kim, Jae Kyeong
    • Journal of Intelligence and Information Systems
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    • v.19 no.1
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    • pp.79-94
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    • 2013
  • Recently, the high value added business is steadily growing in the culture and art area. To generated high value from a performance, the satisfaction of audience is necessary. The flow in a critical factor for satisfaction, and it should be induced from audience and measures. To evaluate interest and emotion of audience on contents, producers or investors need a kind of index for the measurement of the flow. But it is neither easy to define the flow quantitatively, nor to collect audience's reaction immediately. The previous studies of the group flow were evaluated by the sum of the average value of each person's reaction. The flow or "good feeling" from each audience was extracted from his face, especially, the change of his (or her) expression and body movement. But it was not easy to handle the large amount of real-time data from each sensor signals. And also it was difficult to set experimental devices, in terms of economic and environmental problems. Because, all participants should have their own personal sensor to check their physical signal. Also each camera should be located in front of their head to catch their looks. Therefore we need more simple system to analyze group flow. This study provides the method for measurement of audiences flow with group synchronization at same time and place. To measure the synchronization, we made real-time processing system using the Differential Image and Group Emotion Analysis (GEA) system. Differential Image was obtained from camera and by the previous frame was subtracted from present frame. So the movement variation on audience's reaction was obtained. And then we developed a program, GEX(Group Emotion Analysis), for flow judgment model. After the measurement of the audience's reaction, the synchronization is divided as Dynamic State Synchronization and Static State Synchronization. The Dynamic State Synchronization accompanies audience's active reaction, while the Static State Synchronization means to movement of audience. The Dynamic State Synchronization can be caused by the audience's surprise action such as scary, creepy or reversal scene. And the Static State Synchronization was triggered by impressed or sad scene. Therefore we showed them several short movies containing various scenes mentioned previously. And these kind of scenes made them sad, clap, and creepy, etc. To check the movement of audience, we defined the critical point, ${\alpha}$and ${\beta}$. Dynamic State Synchronization was meaningful when the movement value was over critical point ${\beta}$, while Static State Synchronization was effective under critical point ${\alpha}$. ${\beta}$ is made by audience' clapping movement of 10 teams in stead of using average number of movement. After checking the reactive movement of audience, the percentage(%) ratio was calculated from the division of "people having reaction" by "total people". Total 37 teams were made in "2012 Seoul DMC Culture Open" and they involved the experiments. First, they followed induction to clap by staff. Second, basic scene for neutralize emotion of audience. Third, flow scene was displayed to audience. Forth, the reversal scene was introduced. And then 24 teams of them were provided with amuse and creepy scenes. And the other 10 teams were exposed with the sad scene. There were clapping and laughing action of audience on the amuse scene with shaking their head or hid with closing eyes. And also the sad or touching scene made them silent. If the results were over about 80%, the group could be judged as the synchronization and the flow were achieved. As a result, the audience showed similar reactions about similar stimulation at same time and place. Once we get an additional normalization and experiment, we can obtain find the flow factor through the synchronization on a much bigger group and this should be useful for planning contents.