• 융합신호처리학회논문지
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• 제15권4호
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• pp.135-140
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• 2014

디지털 영상 장치의 이용이 증가함에 따라, 영상 처리 관련 소프트웨어 및 하드웨어에 대한 관심이 높아지고 있으며, 영상 처리는 물체 인식, 물체 검출, 지문 인식 등의 여러 분야에서 적용되고 있다. 에지 검출은 대부분의 영상 처리 기술 등의 전처리 과정으로 국내외에서 많은 연구가 진행되고 있다. 대표적인 에지 검출 방법에는 소벨(Sobel), 프리윗(Prewitt), 라플라시안(Laplacian), 로버츠(Roberts), 케니(Canny) 에지 검출기 등이 있으며, 이러한 기존의 방법들은 비잡음 영상에서 에지를 우수하게 검출이 가능하나 임펄스 잡음에 훼손된 영상에서는 잡음 제거 특성이 미흡하여, 에지 검출 특성이 미흡하게 나타난다. 따라서 본 논문에서는 임펄스 잡음에 훼손된 영상에서 우수한 에지 검출 특성을 얻기 위하여, 마스크의 중심 화소를 축으로 하여 4개의 영역으로 나누고, 각 영역의 대표 화소값에 따라 추정 화소를 구하며, 추정된 마스크와 새로운 방향성 마스크를 적용하여 최종 에지를 검출하는 알고리즘을 제안하였다.

• 한국정보통신학회논문지
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• 제18권12호
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• pp.2982-2988
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• 2014

에지 검출은 영상 분할, 영상 인식 등의 전처리 과정이며, 국내외에서 많은 관련 연구가 진행되고 있다. 대표적인 에지 검출 방법에는 소벨(Sobel), 프리윗(Prewitt), 라플라시안(Laplacian), 로버츠(Roberts), 케니(Canny) 에지 검출기 등이 있으며, 이러한 기존의 방법들은 비잡음 영상에서 에지를 검출할 경우 에지를 우수하게 검출이 가능하나 salt-and-pepper 잡음에 훼손된 영상에서는 잡음의 영향에 의해 에지 검출 특성이 미흡하게 나타난다. 따라서 본 논문은 salt-and-pepper 잡음에 훼손된 영상에서 우수한 에지 검출 특성을 얻기 위하여, 먼저 마스크의 중심 화소를 기준으로 상, 하, 좌, 우 방향으로 영역을 구분한다. 그리고 각 영역의 대표 화소값의 잡음 여부를 판단하여 그 결과에 따라 추정 마스크의 요소를 구한 후, 여기에 방향성 마스크를 적용하여 최종 에지를 검출하는 알고리즘을 제안하였다.

• 대한원격탐사학회지
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• 제31권5호
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• pp.395-408
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• 2015

고해상도 위성영상 모자이크는 두 장 이상의 위성영상을 공간적으로 합성하여 보다 넓은 단일 영상을 만드는 영상 처리 과정으로 원격탐사 분야에서 그 중요성이 날로 커지고 있다. 본 연구에서는 영상 모자이크 작업 시 요구되는 접합선 자동 추출기법과 이를 기반으로 한 모자이크 영상 제작 방법을 제시하였다. 대용량인 고해상도 위성영상에서 보다 빠르고 효율적인 접합선 추출하기 위해서, NDVI의 특성을 활용하여 빠르게 경계선을 추출하는 NDVI 기반 접합선 추출 알고리즘을 개발하였다. NDVI는 식생의 분포량 및 활동성을 나타내는 정규화 식생지수로 이를 활용하여 인공지역과 자연지역을 분리하여 초기 접합선을 추출하였다. Canny 에지 연산자를 적용하여 비용범위이미지를 생성하고, 초기 접합선을 기준으로 버퍼링 기법을 사용하여 범위 비용 이미지를 생성하였다. 다익스트라 알고리즘을 사용하여 접합선을 추출하고, 획득시기가 다른 인접영상간의 방사 왜곡을 줄이기 위하여 히스토그램 매칭을 수행하였다. KOMPSAT-2/3 위성영상을 이용한 실험결과, 두 영상의 기하학적 차이로 인한 시각적 불연속 특징이 감소됨을 확인할 수 있었고, 접합선 추출시 소요되는 연산시간이 감소되는 것을 확인할 수 있었다.

• 한국염색가공학회지
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• 제20권1호
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• pp.48-56
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• 2008

A real-time inspection system has been developed by combining CCD based image processing algorithm and a standard lighting equipment. The system was tested for defective fabrics showing nozzle contact scratch marks, which are one of the frequently occurring defects. Two algorithms used were compared according to both their processing time and detection rate. First algorithm (algorithm A) was based on morphological image processing such as dilation and opening for effective treatment of defective printing areas while second one (algorithm B) mainly employs well-defined edge detection technique based on canny detector and Zermike moment. It was concluded' that although both algorithms were quite successful, algorithm B showed relatively consistent performance than algorithm A in detecting complex patterns.

• 산업공학
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• 제21권4호
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• pp.394-402
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• 2008

The objective of this paper is to design segmentation algorithm for applying the breast ultrasound image to CAD(Computer Aided Diagnosis). This study is conducted after understanding limits, used algorithm and demands of CAD system by interviewing with a medical doctor and analyzing related works based on a general CAD framework that is consisted of five step-establishment of plan, analysis of needs, design, implementation and test & maintenance. Detection function of CAD is accomplished by Canny algorithm and arithmetic operations for segmentation. In addition to, long computing time is solved by extracting ROI (Region Of Interests) and applying segmentation technical methods based morphology algorithm. Overall course of study is conducted by verification of medical doctor. And validity and verification are satisfied by medical doctor's confirmation. Moreover, manual segmentation of related works, restrictions on the number of tumor and dependency of image resolution etc. was solved. This study is utilized as a support system aided doctors' subjective diagnosis even though a lot of future studies is needed for entire application of CAD system.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.234-237
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• 2007

Road networks are important geospatial databases for various GIS (Geographic Information System) applications. Road digital maps may contain geometric spatial errors due to human and scanning errors, but manually updating roads information is time consuming. In this paper, we developed a new road features updating methodology using from multispectral high-resolution satellite image and pre-existing vector map. The approach is based on initial seed point generation using line segment matching and a modified double snake algorithm. Firstly, we conducted line segment matching between the road vector data and the edges of image obtained by Canny operator. Then, the translated road data was used to initialize the seed points of the double snake model in order to refine the updating of road features. The double snake algorithm is composed of two open snake models which are evolving jointly to keep a parallel between them. In the proposed algorithm, a new energy term was added which behaved as a constraint. It forced the snake nodes not to be out of potential road pixels in multispectral image. The experiment was accomplished using a QuickBird pan-sharpened multispectral image and 1:5,000 digital road maps of Daejeon. We showed the feasibility of the approach by presenting results in this urban area.

• 반도체디스플레이기술학회지
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• 제11권1호
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• pp.79-83
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• 2012

We use adaptive method and determine threshold coefficient so that the algorithm could decide a suitable binarization threshold coefficient of the image to detecting a marker; therefore, we solve the light influence on the shadow area and dark region. In order to improve the speed for reducing computation we created Integral Image. The algorithm detects an outline of the image by using canny edge detection for getting damage or obscured markers as it receives the noise removed picture. The strength of the line of the outline is extracted by Hough transform and it extracts the candidate regions corresponding to the coordinates of the corners. Markers extracted using the equation of a straight edge to find the coordinates. By using the equation of straight the algorithm finds the coordinates the corners. of extracted markers. As a result, even if all corners are obscured, the algorithm can find all of them and this was proved through the experiment.

• Ocean Systems Engineering
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• 제2권2호
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• pp.137-145
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• 2012

Recent developments in underwater image recognition methods have received large attention by the ocean engineering researchers. In this paper, an improved bi-dimensional empirical mode decomposition (BEMD) approach is employed to decompose the given underwater image into intrinsic mode functions (IMFs) and residual. We developed a joint algorithm based on BEMD and Canny operator to extract multi-pixel edge features at multiple scales in IMFs sub-images. So the multiple pixel edge extraction is an advantage of our approach; the other contribution of this method is the realization of the bi-dimensional sifting process, which is realized utilizing regional-based operators to detect local extreme points and constructing radial basis function for curve surface interpolation. The performance of the multi-pixel edge extraction algorithm for processing underwater image is demonstrated in the contrast experiment with both the proposed method and the phase congruency edge detection.

• Journal of information and communication convergence engineering
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• 제12권3호
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• pp.193-197
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• 2014

Edges are a robust feature for object detection. In this paper, we present an edge-based background modeling method for the detection of moving objects. The edges in the image frames were mapped using robust Canny edge detector. Two edge maps were created and combined to calculate the ultimate moving-edge map. By selecting all the edge pixels of the current frame above the defined threshold of the ultimate moving edges, a temporary background-edge map was created. If the frequencies of the temporary background edge pixels for several frames were above the threshold, then those edge pixels were treated as background edge pixels. We conducted a performance comparison with previous works. The existing edge-based moving-object detection algorithms pose some difficulty due to the changes in background motion, object shape, illumination variation, and noises. The result of the performance evaluation shows that the proposed algorithm can detect moving objects efficiently in real-world scenarios.

• 전기학회논문지
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• 제59권8호
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• pp.1477-1481
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• 2010

In this paper, we propose the classification and tracking method of the hand region using deformable template and condensation. To do this, first, we extract the hand region by using the fuzzy color filter and HCbCr color model. Second, we extract the edge of hand by applying the Canny edge algorithm. Third, we find the first template by calculating the conditional probability between the extracted edge and the model edge. If the accurate template of the first object is decided, the condensation algorithm tries to track it. Finally, we demonstrate the effectiveness and feasibility of the proposed method through some experiments.