• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.359-362
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• 2004

In multi-dimensional image, ICA-based feature extraction algorithm, which is proposed in this paper, is for the purpose of detecting target feature about pixel assumed as a linear mixed spectrum sphere, which is consisted of each different type of material object (target feature and background feature) in spectrum sphere of reflectance of each pixel. Landsat ETM+ satellite image is consisted of multi-dimensional data structure and, there is target feature, which is purposed to extract and various background image is mixed. In this paper, in order to eliminate background features (tidal flat, seawater and etc) around target feature (laver farm) effectively, pixel spectrum sphere of target feature is projected onto the orthogonal spectrum sphere of background feature. The rest amount of spectrum sphere of target feature in the pixel can be presumed to remove spectrum sphere of background feature. In order to make sure the excellence of feature extraction method based on ICA, which is proposed in this paper, laver farm feature extraction from Landsat ETM+ satellite image is applied. Also, In the side of feature extraction accuracy and the noise level, which is still remaining not to remove after feature extraction, we have conducted a comparing test with traditionally most popular method, maximum-likelihood. As a consequence, the proposed method from this paper can effectively eliminate background features around mixed spectrum sphere to extract target feature. So, we found that it had excellent detection efficiency.

• 전자공학회논문지S
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• 제34S권10호
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• pp.104-111
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• 1997

It is known as a difficult problem to recognize text-background mixed documents. In this paper a new string extraction algorithm, using mathematical morphology for the document consisting of text and overlapped periodic background pattern, is proposed. The algorithm consists of pattern periodicity feature extraction and background removal. The extracted pattern periodicity feature is used to determine the shape of structuring elements for morphological pre- and post-processing to remove background. The effectiveness of the proposed algorithm over the existing one is also verified through the experiments with various test documents.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(3)
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• pp.141-144
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• 2001

In this paper, a new algorithm for extracting and recognizing characters from video, without pre-knowledge such as font, color, size of character, is proposed. To improve the recognition rate for videos with complex background at low resolution, continuous frames with identical text region are automatically detected to compose an average frame. Using boundary pixels of a text region as seeds, we apply region filling to remove background from the character Then color clustering is applied to remove remaining backgrounds according to the verification of region filling process. Features such as white run and zero-one transition from the center, are extracted from unknown characters. These feature are compared with a pre-composed character feature set to recognize the characters.

• Journal of Information Technology Applications and Management
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• 제30권1호
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• pp.11-19
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• 2023

To remove unnecessary background from tooth X-ray images and enhance the sharpness of tooth and gum images, image processing techniques including contrast adjustment and histogram equalization are used. The introduction of two methods for detecting the boundary of the tooth and gum region and separating the tooth and gum from the background. In both cases, the background of the tooth X-ray images could be removed as a result, improving the quality of the images. The proposed method improves MTF (Modulation Transfer Function), an image performance indicator, as a result of measuring MTF. The original image's spatial frequency ranged from 4.73 to 11.40 lp/mm at the 10% response, whereas the proposed image's spatial frequency ranged from 10.90 to 11.85 lp/mm, giving uniformly enhanced results. In contrast, tooth and gums could not be completely separated from the background using Apple's Lift subject from background function.

• 한국융합학회논문지
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• 제10권5호
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• pp.27-34
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• 2019

본 논문에서는 문자 영역의 패턴을 분석하여 배경 영역을 제거하는 방법을 제안하였다. 명암이 일정한 영역을 구분하는 MSER(Maximally Stable External Regions)방법의 문자 검출에서는 배경 영역이 포함되어 검출되었다. 이러한 문제점을 해결하기 위해 자연 이미지에서 MSER 방법을 사용하여 명암 값이 차이가 나는 영역과 차이가 나지 않는 영역 즉 문자 영역과 배경 영역을 구해 변화율을 계산하여 배경을 제거하였다. 그러나 배경이 제거된 이미지에서 일부 제거되지 않는 배경 영역이 생겨 LBP(Local Binary Patterns)방법을 사용하여 이미지에서 균일한 값을 갖는 영역을 문자 영역이라고 판단하고 문자를 검출하였다. 실험 데이터는 배경이 단순한 이미지, 문자가 정면으로 구성된 이미지, 문자가 기울어진 이미지 등의 다양한 자연 이미지를 실험하였다. 제안하는 방법을 기존의 MSER, MSER+LBP 방법의 문자 검출 방법과 비교하였을 때 약 1.73%로 높은 검출률을 보였다.

• 한국산학기술학회논문지
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• 제13권5호
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• pp.2291-2297
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• 2012

X-선 스펙트럼 데이터는 물질의 성분과 관련이 없는 신호(백그라운드, 노이즈)들을 포함 하고 있다. XRF는 스펙트럼에서 가우시안 형태의 피크 위치와 크기를 이용하여 시료의 성분을 분석하며, 시료의 성분을 정확히 분석하기 위해서는 노이즈와 백그라운드를 제거 하여야 한다. 백그라운드를 제거하기 위한 방법으로는 SNIP, Threshold, Morphology 방법 등을 적용하고 있으며, Threshold 기법을 중에서 블록별로 각기 다른 임계값을 적용하는 Interval Threshold기법이 하나의 임계값을 적용하는 Level Threshold 방법보다 더 좋은 성능을 발휘한다. 본 논문에서는 Interval Threshold를 적용하기 위하여 웨이블릿을 이용하여 블록을 분리하는 알고리즘을 제안하였다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집B
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• pp.670-675
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• 2001

This paper is to propose image segmentation method based on chamfer algorithm. First, we get original image from CCD camera and transform it into gray image. Second, we extract maximum gray value of background and reconstruct and eliminate the background using surface fitting method and bilinear interpolation. Third, we subtract the reconstructed background from gray image to remove noises in gray image. Fourth, we transform the subtracted image into binary image using Otsu's optimal thresholding method. Fifth, we use morphological filters such as areaopen, opening, filling filter etc. to remove noises and isolated points. Sixth, we use chamfer distance or Euclidean distance to this filtered image. Finally, we use watershed algorithm and count microorganisms in image by labeling. To prove the effectiveness, we apply the proposed algorithm to one of Ammonia-oxidizing bacteria, Acinetobacter sp. It is shown that both Euclidean algorithm and chamfer algorithm show over-segmentation. But Chamfer algorithm shows less over-segmentation than Euclidean algorithm.

• 대한기관식도과학회지
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• 제7권1호
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• pp.14-18
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• 2001

Background and Objectives： Vegetable Foreign bodies (VFB) in the bronchial tree may be complicated by fragmentation, slippage and impaction during the removal with forceps. This study is to evaluate the safety and efficacy for the technique of removing VFB from the bronchial tree in infants and early childhood using Fogarty balloon catheter. Materials and methods : The subjects consisted of 18 infants and early childhood (7-22 months old) with VFB in the bronchial tree from January 1991 through October 1998. The authors first attempted removal of VFB with forceps and if that failed, removed VFB with Fogarty arterial embolectomy catheter under the ventilating bronchoscopy and general anesthesia. Results: We removed 6 VFB with forceps. could not remove anymore, and so removed 12 VFB with Fogarty catheter. In 8 VFB of less than 24 hours, we could remove 6 VFB with forceps and 2 VFB which could not be removed with forceps were removed with Fogarty catheter. In 10 VFB of more than 24 hours, we could not remove with forceps and removed with Fogarty catheter. Conclusions : VFB in the bronchial tree of infants and early childhood can usually be removed with forceps. But we think that Fogarty balloon catheter technique is a easy, safe method for the removal of bronchial VFB of more than 24 hours, fragmentation, impaction, lower bronchus and too round or slippery to remove with forceps in infants and early childhood.

• 전자공학회논문지C
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• 제34C권1호
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• pp.51-58
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• 1997

In passive sonar, the frequency spectrum of a sound radiated by underwater moving targets is composed of a broadband nonuniform background noise and narrowband discrete tonals. To detect the tonals, the background noise is estimated and removed. Using the existing algorithms that estimate the background noise, a week tonals are not detected. Because a freuqency line that is formed by tonals which are being extracted continuously is a feture of the target, we are nessesory to efficiently detect the tonals that compose the frequncy line. In this paper, we propose an efficient neural network that can remove automatically the background and detect the even errl tonals, and we extract the frequency line feature on the spectrogram by the proposed algorithm. The experimental results for a ship's radiated sound show a better performance in comparison with the existing TPM algorithm.

• Fisheries and Aquatic Sciences
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• 제4권1호
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• pp.10-17
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• 2001

One serious problem among the troubles to identify objects in an optical microscopic image is contour background due to non-uniform light source and various transparency of samples. To solve this problem, this paper proposed an elimination method of the contour background and compensation technique as follows. First, Otsu's optimal thresholding method extracts pixels representing background. Second, bilinear interpolation finds non-deterministic background pixels among the sampled pixels. Third, the 2D cubic fitting method composes surface function from pivoted background pixels. Fourth, reconstruction procedure makes a contour image from the surface function. Finally, elimination procedure subtracts the approximated background from the original image. To prove the effectiveness of the proposed algorithm, this algorithm is applied to the yeast Zygosaccharomyces rouxii and ammonia-oxidizing bacteria Acinetobacter sp. Labeling by this proposed method can remove some noise and is more exact than labeling by only Otsu's method. Futhermore, we show that it is more effective for the reduction of noise.