• Nuclear Engineering and Technology
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• 제56권6호
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• pp.2057-2062
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• 2024

Among photon counting detector (PCD)-based technologies, the K-edge subtraction (KES) method has a very high material decomposition efficiency. Yet, since the increase in noise in the X-ray image to which the KES method is applied is inevitable, research on image quality improvement is essential. Here, we modeled a block-matching and 3D filtering (BM3D) algorithm and applied it to PCD-based X-ray images with the improved KES (IKES) method. For PCD modeling, Monte Carlo simulation was used, and a phantom composed of iodine substances with different concentrations was designed. The IKES method was modeled by adding a log term to KES, and the X-ray image used for subtraction was obtained by applying the 3.0 keV range based on the K-edge region of iodine. As a result, the IKES image using the BM3D algorithm showed the lowest normalized noise power spectrum value. In addition, we confirmed that the contrast-to-noise ratio and no-reference-based evaluation results when the BM3D algorithm was applied to the IKES image were improved by 29.36 % and 20.56 %, respectively, compared to the noisy image. In conclusion, we demonstrated that the IKES imaging technique using a PCD-based detector and the BM3D algorithm fusion technique were very efficient for X-ray imaging.

• 대한방사선기술학회지:방사선기술과학
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• 제7권1호
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• pp.13-21
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• 1984

Subtraction is an essential technic to improve imaging quality in various radiological procedures. The limitations of subtraction, however, are well known. Blurred under-subtraction (BUS) method has been suggested to overcome and compensate these limitations. Ten cases of angiography were subtracted by conventional subtraction and BUS technic. Results of this study revealed that BUS method is simple to perform and imaging quality obtained by BUS is excellent. Comparing to conventional subtraction, BUS method has advantages. For example, BUS need no mask film or no immobilization of patient during examination. Improvement of imaging Qualify is achieved by edge enhancement, homogeneous blurring of background density and increasing contrast. With emphasis of its simplicity in technic, we would report that BUS method is a useful adjunct imaging technic in various radiological procedures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권4호
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• pp.782-804
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• 2011

In video-based recognition systems, stationary cameras are used to monitor an area of interest. These systems focus on a segmentation of the foreground in the video stream and the recognition of the events occurring in that area. The usual approach to discriminating the foreground from the video sequence is background subtraction. This paper presents a novel background subtraction method based on a probabilistic approach. We represent the posterior probability of the foreground based on the current image and all past images and derive an updated method. Furthermore, we present an efficient fusion method for the color and edge information in order to overcome the difficulties of existing background subtraction methods that use only color information. The suggested method is applied to synthetic data and real video streams, and its robust performance is demonstrated through experimentation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권10호
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• pp.4092-4107
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• 2015

We propose a background subtraction method for moving cameras based on trajectory classification, image segmentation and label inference. In the trajectory classification process, PCA-based outlier detection strategy is used to remove the outliers in the foreground trajectories. Combining optical flow trajectory with watershed algorithm, we propose a trajectory-controlled watershed segmentation algorithm which effectively improves the edge-preserving performance and prevents the over-smooth problem. Finally, label inference based on Markov Random field is conducted for labeling the unlabeled pixels. Experimental results on the motionseg database demonstrate the promising performance of the proposed approach compared with other competing methods.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.477-480
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• 2005

In this paper, we propose a preprocess method to needs for Car License Plate Recognition on poor environment. This preprocess method use multi images to get low value to compare images value. Last method was Opening operation that Using Edge pixel to add and subtraction. The Result was removed White pixel and very mini feather. But This method needs many process times and License Plate Recognition is low quality problem. Another method is median filter and conversion. This paper key idea that rain & snow is high value. So This paper propose get low value to compare image value.

• 대한전자공학회논문지TC
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• 제40권6호
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• pp.213-224
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• 2003

제안된 알고리듬은 채널 잡음전력에 따라 적응적으로 문턱값 레벨을 결정하는 적응 문턱값 설정방식을 사용하여 채널특성에 관계없이 항상 최적의 문턱값을 설정한다. 또한, 이것은 그 추정성능이 다중경로채널에서의 전력지연 프로파일 변동에 대해 덜 민감하도록 만드는 특별하게 설계된 훈련심볼을 사용한다. 그 결과, 제안된 기법의 추정성능은 채널특성 변동에 대해 영향을 적게 받는다.

• 한국항행학회논문지
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• 제12권2호
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• pp.164-169
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• 2008

본 논문에서는 영상분할에 의한 동작 추적 기법을 이용하여 침입자를 감시하고 관련 정보를 모바일 기반으로 확인하도록 하였다. 먼저, 탐지하고자 하는 일정한 영역을 촬영한 동영상에서 프레임을 추출하고, 인접한 두 프레임 사이의 이미지 차를 사용하여, 고정된 배경과 움직이는 대상을 분할한다. 분할된 전경 물체에서 에지를 검출하여 지정된 위치별로 추출된 에지의 중간 값을 추정하여 동작을 분석함으로써 침입자를 감시할 수 있도록 하였다. 동작이 검출되면, 영상은 WAP 풀 기반 영상 전송 방법을 사용하여 모바일 클라이언트로 전송한다.

• Journal of Biosystems Engineering
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• 제27권4호
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• pp.341-348
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• 2002

Quality evaluation of red ginsengs is determined by outer shape and inner qualities. Especially, the inner qualities are main grading criteria. Currently, red ginsengs are classified into 3-grades; heaven, earth and good. The best heaven grade must not include inner holes and sponge tissues. This study was conducted to develop a red ginseng sorting system using x-ray image processing technique. Because of lens characteristic, gray values of the central region in the x-ray image are higher and gradually decreased towards the edge regions. This difference of gray values gives trouble in segmentation and detection of inner holes in red ginseng image, so preprocessing technique is necessary. The preprocessing was done by subtracting source image from an empty background image. But, simple subtraction was not quite appropriate because of too small contrast between inner holes and sound part. Scaled subtraction images were obtained by multiplying all gray values by some numbers. However this method could not help to set threshold value because the gray values of root part are generally lower than body part when red ginseng is exposed to the x-ray. To determine threshold value for detecting inner holes, an algorithm was developed by increasing overall gray values of less clear images.

• 전자공학회논문지SC
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• 제38권5호
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• pp.42-51
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• 2001

차량검출은 교통량 관측을 위해서 필요한 가장 기본적인 요소이다. 영상을 기반으로 한 교통정보 추출 시스템은 다른 방식을 이용하는 시스템들과 비교했을 때 몇 가지 두드러진 장점을 가지고 있다. 그러나, 영상기반 시스템에서는 영상에 포함된 그림자가 차량검출의 정확도를 저해하는 요소로 작용하는 데, 특히 이동중인 차량에 의해서 발생하는 활성 그림자는 심각한 성능저하를 야기할 수 있다. 본 논문에서는 차량검출과 그림자 영향 제거를 위해서 배경 빼기와 에지 검출을 결합한 새로운 접근방법을 제안하였다. 제안한 방법은 노변의 지형지물에 의해서 발생하는 비활성 그림자가 크게 증가하는 상황에서도, 98[%]이상의 차량검출 정확도를 나타내었다. 본 논문에서 제안한 차량검출 방법을 기반으로 하여, 차량 추적, 차량 계수, 차종 분류, 그리고 속도 측정을 수행하여 각 차선의 부하를 나타내는 데 사용되는 차량 흐름과 관련된 여러 가지 교통정보를 추출하였다.