• Journal of Information Processing Systems
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• 제16권6호
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• pp.1424-1436
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• 2020

Although huge progress has been made in current image segmentation work, there are still no efficient segmentation strategies for tree image which is taken from natural environment and contains complex background. To improve those problems, we propose a method for tree image segmentation combining adaptive mean shifting with image abstraction. Our approach perform better than others because it focuses mainly on the background of image and characteristics of the tree itself. First, we abstract the original tree image using bilateral filtering and image pyramid from multiple perspectives, which can reduce the influence of the background and tree canopy gaps on clustering. Spatial location and gray scale features are obtained by step detection and the insertion rule method, respectively. Bandwidths calculated by spatial location and gray scale features are then used to determine the size of the Gaussian kernel function and in the mean shift clustering. Furthermore, the flood fill method is employed to fill the results of clustering and highlight the region of interest. To prove the effectiveness of tree image abstractions on image clustering, we compared different abstraction levels and achieved the optimal clustering results. For our algorithm, the average segmentation accuracy (SA), over-segmentation rate (OR), and under-segmentation rate (UR) of the crown are 91.21%, 3.54%, and 9.85%, respectively. The average values of the trunk are 92.78%, 8.16%, and 7.93%, respectively. Comparing the results of our method experimentally with other popular tree image segmentation methods, our segmentation method get rid of human interaction and shows higher SA. Meanwhile, this work shows a promising application prospect on visual reconstruction and factors measurement of tree.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권11호
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• pp.2893-2912
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• 2013

The design of geometrically invariant watermarking is one of the most challenging work in digital image watermarking research area. To achieve the robustness to geometrical attacks, the inherent characteristic of an image is usually used. In this paper, a geometrically invariant image watermarking scheme using connected objects and gravity center is proposed. First, the gray-scale image is converted into the binary one, and the connected objects according to the connectedness of binary image are obtained, then the coordinates of these connected objects are mapped to the gray-scale image, and the gravity centers of those bigger objects are chosen as the feature points for watermark embedding. After that, the line between each gravity center and the center of the whole image is rotated an angle to form a sector, and finally the same version of watermark is embedded into these sectors. Because the image connectedness is topologically invariant to geometrical attacks such as scaling and rotation, and the gravity center of the connected object as feature points is very stable, the watermark synchronization is realized successfully under the geometrical distortion. The proposed scheme can extract the watermark information without using the original image or template. The simulation results show the proposed scheme has a good invisibility for watermarking application, and stronger robustness than previous feature-based watermarking schemes against geometrical attacks such as rotation, scaling and cropping, and can also resist common image processing operations including JPEG compression, adding noise, median filtering, and histogram equalization, etc.

• Journal of Radiation Protection and Research
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• 제35권1호
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• pp.26-33
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• 2010

비파괴검사 분야의 방사선 검사(RT) 방식은 image plate (IP)를 사용한 Computed Radiography(CR) 영상시스템의 도입에 따라 필름 방식의 아날로그 영상이 점차 디지털 영상으로 교체되고 있다. 비파괴검사에서 결함을 효과적으로 검출할 수 있는 영상의 품질은 촬영 조건, 영상획득매체, 사용 선원의 종류 및 촬영 거리, 검사체 두께등이 영향을 미친다. 본 논문에서는 비파괴 검사 분야에 적용할 수 있는 감마선원의 기본 특성을 조사하였고, FUJI사에서 개발한 CR 영상 시스템에 $^{75}Se$, $^{192}Ir$ 동위원소를 적용하여 영상을 획득하였다. 획득된 영상의 gray scale을 이미지 소프트웨어를 통해 추출한 후에 대조도 및 신호대잡음비를 계산하고 비교 분석하였다. 또한 투과도계를 이용한 비교 영상을 통하여 식별도를 분석하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권2호
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• pp.155-160
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• 2004

In this paper, we describe the results of a study on the edge enhancement of X-ray images by using their fuzzy system representation. A set of gray scale X-ray images was generated using the EGS4 computer code. An aluminum plate or a lead plate with three parallel strips taken out has been used as the object with the thickness and the width of the plate, and the gap between the two strips varied. We started with a comparative study on a set of the fuzzy sets for their applicability as the input fuzzy sets for the fuzzy system representation of the gray scale images. Then we describe how the fuzzy system is used to sharpen the edges. Our algorithm is based on adding the magnitude of the gradient not to the pixel value of concern but rather to the nearest neighboring pixel in the direction of the gradient. We show that this algorithm is better in maintaining the spatial resolution of the original image after the edge enhancement.

• 한국정밀공학회지
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• 제20권8호
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• pp.108-114
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• 2003

This research describes a image-processing technique for the scratch detecting algorithm for ITO coated glass. We use the modified logical thresholding method (called adaptive logical thresholding method) for binarization of gray-scale glass image. This method is useful to the algorithm for detecting the scratch of ITO coated glass automatically without need of any prior information of manual fine-tuning of parameters.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2002년도 International Meeting on Information Display
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• pp.849-851
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• 2002

This research describes a image-processing technique for the scratch detecting algorithm for ITO coated glass. We use the modified logical thresholding method for binarization of gray-scale glass image. This method is useful to the algorithm for detecting the scratch of ITO coated glass automatically without need of any prior information of manual fine-tuning of parameters.

• 대한전자공학회논문지SP
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• 제43권5호
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• pp.30-36
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• 2006

변형된 면적기반영역선별 기법으로 문자영상 속에 내재되어 있던 영역 분할을 회복하는 새로운 기법을 제안한다. 정보영역과 바탕영역으로 양분되어 있는 이진 원영상에 비해 오염 및 훼손으로 관측영상은 얼룩점과 잡음이 전체 영상에 섞여 다수의 크고 작은 영역들이 혼재된 그레이스케일 형태가 된다. 이러한 영상을 종래의 문턱치 처리나 확률적 기법으로 영역 분할하려면 이진영상으로 전환시킴에 의한 영역 형태 변형 문제가 발생한다. 이 문제를 최소화하기 위해 마름모꼴 블록을 채택한 반복조건부양식(iterated conditional mode, ICM) 기법으로 이진 영상을 구현하여 일차적으로 영역들의 집합으로 분류하였다. 그 다음 현재고려중인 화소에서 화소의 영역형성 판별과 영역의 면적을 산출하였다. 이를 전체 화소에 걸쳐 순차적으로 확산하여 해당영역들의 정보영역으로의 귀속 여부를 선택적으로 판정 분할함으로 정보영역 본래 형태를 복원하였다. 이 때 지정 영역들의 산출 면적들은 하나의 집합으로 배속 정렬되며 확률처리로 얻은 판별 파라미터 값에 의해 선별된다. 그레이스케일 탁본영상을 대상으로 종래의 문턱치 영역분할 기법과 ICM 기법도 함께 실험하였다. 그 결과 종래의 기법에 비해 우수한 영역분할 효과를 얻을 수 있었다.

• 한국인쇄학회지
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• 제16권2호
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• pp.45-59
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• 1998

Halftonig is a technique to create the appearance of intermideate tone levels by controlling the spatial distribution of the binary pixel values. Recently, many printing devices such as image setter, inkjet printer, laser printer and facsimile, generate image, they require the technique. Ordered dither is achieved comparing the gray scale image to periodic array. This method is fast, but it occurs periodic patterns. Conentional error diffusion generates a good image. But processing speed is very slow and appeares worm artifacts in middle tone scale. To improve it, Bns(Blue noise Screen) is developed based on Gaussian distribution. In this paper, we discribe methods to design BNS based human visual characteristics and to improve blue appearing at edge area of image by USM(using unsharp mask).

• 한국멀티미디어학회논문지
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• 제5권6호
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• pp.609-615
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• 2002

본 논문은 LCD 모니터 상에서 영상 향상을 위한 콘트라스트 제어방식을 제안하였다. 제안한 방식은 입력되는 필드 혹은 프레임 중에서 화소의 최대 값과 최소 값을 판별하고 이를 이용하여 화면의 개선 정도를 결정한다. 필드 또는 프레임의 메모리가 필요하지 않고, 기존의 방식에 비해 하드웨어 구성이 간단하여 실시간 처리를 요하는 분야에 쉽게 적용 가능하다 또한 입력되는 콘트라스 영역의 가중치 값을 변화시킴으로써 콘트라스트 제어가 가능하다 제안한 방법은 콘트라스트 제어 알고리즘과 룩업 테이블을 이용한 영상의 모드에 따라선택적으로 가중치 기울기를 구간별로 달리하여 개선된 영상을 얻는다. 제안한 다계조 콘트라스트 제어 방식을 컴퓨터 시뮬레이션을 통하여 검증하였으며, 시뮬레이션을 통해 영상을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권4호
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• pp.1543-1561
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• 2020

Taxonomy of human brain activity is a complicated rather challenging procedure. Due to its multifaceted aspects, including experiment design, stimuli selection and presentation of images other than feature extraction and selection techniques, foster its challenging nature. Although, researchers have focused various methods to create taxonomy of human brain activity, however use of multivariate pattern analysis (MVPA) for image recognition to catalog the human brain activities is scarce. Moreover, experiment design is a complex procedure and selection of image type, color and order is challenging too. Thus, this research bridge the gap by using MVPA to create taxonomy of human brain activity for different categories of images, both colored and gray scale. In this regard, experiment is conducted through EEG testing technique, with feature extraction, selection and classification approaches to collect data from prequalified criteria of 25 graduates of University Technology PETRONAS (UTP). These participants are shown both colored and gray scale images to record accuracy and reaction time. The results showed that colored images produces better end result in terms of accuracy and response time using wavelet transform, t-test and support vector machine. This research resulted that MVPA is a better approach for the analysis of EEG data as more useful information can be extracted from the brain using colored images. This research discusses a detail behavior of human brain based on the color and gray scale images for the specific and unique task. This research contributes to further improve the decoding of human brain with increased accuracy. Besides, such experiment settings can be implemented and contribute to other areas of medical, military, business, lie detection and many others.