• 전자공학회논문지B
• /
• 제29B권4호
• /
• pp.36-47
• /
• 1992

In this paper, a set of TM(template matching) mask using the AM(associative mapping) technique was generated and the edge detection algorithm for a SAR image was proposed. And also, the performance of the proposed edge detection algorithm was tested with the conventional edge detection techniques. The proposed edge detection algorithm created an edge image which was more accurate and clear than the conventional edge detection techniques and the performance of the proposed detection technique was not deteriorated for low intensity area in the image because the uncertainly thresholded value genetated by the conventional detection methods was requested. Also, the number of masks and the detection time were reduced by adjusting resolution of edge detection and the consideration for the threshold value extracting the edge was very intuitive.

• Current Optics and Photonics
• /
• 제2권1호
• /
• pp.69-78
• /
• 2018

This paper presents a precise edge detection algorithm for the critical dimension (CD) measurement of a Thin-Film Transistor Liquid-Crystal Display (TFT-LCD) pattern. The sigmoid surface function is proposed to model the blurred step edge. This model can simultaneously find the position and geometry of the edge precisely. The nonlinear least squares fitting method (Levenberg-Marquardt method) is used to model the image intensity distribution into the proposed sigmoid blurred edge model. The suggested algorithm is verified by comparing the CD measurement repeatability from high-magnified blurry and noisy TFT-LCD images with those from the previous Laplacian of Gaussian (LoG) based sub-pixel edge detection algorithm and error function fitting method. The proposed fitting-based edge detection algorithm produces more precise results than the previous method. The suggested algorithm can be applied to in-line precision CD measurement for high-resolution display devices.

• Transactions on Electrical and Electronic Materials
• /
• 제17권6호
• /
• pp.363-368
• /
• 2016

Rectangular shape detection plays an important role in many image recognition systems. However, it requires continued research for its improved performance. In this study, we propose a strong rectangular shape detection algorithm, which combines the canny edge and line detection algorithms based on the perpendicularity and parallelism of a rectangle. First, we use the canny edge detection algorithm in order to obtain an image edge map. We then find the edge of the contour by using the connected component and find each edge contour from the edge map by using a DP (douglas-peucker) algorithm, and convert the contour into a polyline segment by using a DP algorithm. Each of the segments is compared with each other to calculate parallelism, whether or not the segment intersects the perpendicularity intersecting corner necessary to detect the rectangular shape. Using the perpendicularity and the parallelism, the four best line segments are selected and whether a determined the rectangular shape about the combination. According to the result of the experiment, the proposed rectangular shape detection algorithm strongly showed the size, location, direction, and color of the various objects. In addition, the proposed algorithm is applied to the license plate detecting and it wants to show the strength of the results.

• Journal of Information Processing Systems
• /
• 제14권6호
• /
• pp.1331-1346
• /
• 2018

Aiming at the problem that the gradient-based edge detection operators are sensitive to the noise, causing the pseudo edges, a triqubit-state measurement-based edge detection algorithm is presented in this paper. Combing the image local and global structure information, the triqubit superposition states are used to represent the pixel features, so as to locate the image edge. Our algorithm consists of three steps. Firstly, the improved partial differential method is used to smooth the defect image. Secondly, the triqubit-state is characterized by three elements of the pixel saliency, edge statistical characteristics and gray scale contrast to achieve the defect image from the gray space to the quantum space mapping. Thirdly, the edge image is outputted according to the quantum measurement, local gradient maximization and neighborhood chain code searching. Compared with other methods, the simulation experiments indicate that our algorithm has less pseudo edges and higher edge detection accuracy.

• 한국컴퓨터정보학회:학술대회논문집
• /
• 한국컴퓨터정보학회 2008년도 제39차 동계학술발표논문집 16권2호
• /
• pp.211-214
• /
• 2009

Edge detection always influenced by noise belong to the original image, therefore need use some methods to sort this issue, mean shift algorithm has the smooth function which suit for the edge detection purpose, so adopted to fade out the unimportant information, and the sensitive noise portions. After this section, use the Canny algorithm to pick up the contour of the objects we focus on, meanwhile select the Soble operator that has the orientation attribute to support the method work well. In final, take experiment and get the perfect result we wanted, make sure this method make sense and better than the sole Edge detection algorithm,

• 한국정보통신학회:학술대회논문집
• /
• 한국정보통신학회 2013년도 춘계학술대회
• /
• pp.892-894
• /
• 2013

디지털 영상 처리 기술이 발전함에 따라 에지는 여러 응용 분야에서 활용되고 있다. 기존의 에지검출 방법에는 마스크를 이용한 Sobel, Prewitt, Roberts, Laplacian 연산자 등이 있다. 이러한 기존의 방법은 구현이 간단하나, AWGN(additive white Gaussian noise)이 첨가된 영상에서 에지 검출의 오류가 발생한다. 따라서 이와 같은 기존의 방법의 단점을 보완하기 위하여, 본 논문에서는 변형된 마스크를 이용한 에지 검출 알고리즘을 제안하였으며, 제안한 알고리즘은 AWGN 환경에서 우수한 에지검출 특성을 나타내었다.

• 한국정보통신학회:학술대회논문집
• /
• 한국정보통신학회 2015년도 추계학술대회
• /
• pp.328-330
• /
• 2015

에지는 영상에 포함된 물체의 크기, 방향, 위치 등을 쉽게 획득할 수 있는 특징 정보이며, 에지 검출은 물체 검출, 물체 인식 등의 여러 영상 처리 응용 분야에서 전처리 과정으로 활용되고 있다. 기존의 에지 검출 방법에는 Sobel, Prewitt, Roberts 에지 검출 방법 등이 있다. 이러한 기존의 에지 검출 방법들은 구현이 간단하며, 고정 가중치 마스크를 적용하므로 에지 검출 특성이 다소 미흡하다. 따라서 기존의 에지 검출 방법들의 문제점을 보완하기 위하여, 본 논문에서는 국부 마스크 내의 평균 및 표준편차에 따라 가중치를 적용한 후 에지를 검출하는 알고리즘을 제안하였다.

• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• 제27권1호
• /
• pp.37-55
• /
• 2023

In this paper we propose a new algorithm for detecting and counting flowers in a complex background based on digital images. The algorithm mainly includes the following parts: edge contour extraction of flowers, edge contour determination of overlapped flowers and flower counting. We use a contour detection technique in Computer Vision (CV) to extract the edge contours of flowers and propose an improved algorithm with a concave point detection technique to find accurate segmentation for overlapped flowers. In this process, we first use the polygon approximation to smooth edge contours and then adopt the second-order central moments to fit ellipse contours to determine whether edge contours overlap. To obtain accurate segmentation points, we calculate the curvature of each pixel point on the edge contours with an improved Curvature Scale Space (CSS) corner detector. Finally, we successively give three adaptive judgment criteria to detect and count flowers accurately and automatically. Both experimental results and the proposed evaluation indicators reveal that the proposed algorithm is more efficient for flower counting.

• 한국컴퓨터정보학회:학술대회논문집
• /
• 한국컴퓨터정보학회 2008년도 제39차 동계학술발표논문집 16권2호
• /
• pp.207-210
• /
• 2009

Edge detection is an important process in low level image processing. But many proposed methods for edge detection are not very robust to the image noise and are not flexible for different images. To solve the both problems, an algorithm is proposed which eliminate the noise by mean shift algorithm in advance, and then adaptively determine the double thresholds based on gradient histogram and minimum interclass variance, With this algorithm, it can fade out almost all the sensitive noise and calculate the both thresholds for different images without necessity to setup any parameter artificially, and choose edge pixels by fuzzy algorithm.

• 한국산업정보학회논문지
• /
• 제8권4호
• /
• pp.38-45
• /
• 2003

메타 휴리스틱의 한 기법인 Ant System (AS) 알고리듬을 윤곽선 검출 문제에 적용하고 그 실험 결과를 보여준다. 윤곽선의 품질을 픽셀영역간 불일치 정도, 연속성, 두께 및 길이의 관점에서 규정지었다. 적합도 함수를 윤곽선 경로비용 최소화 문제로 전환하여 최적해를 탐색하였다. 예제 영상 실험결과 기존의 다른 기법에 비해, 영상의 질에 무관하게 상대적으로 신속하게 적은 메모리를 차지하는 즉, 최소량의 픽셀로 구성된 윤곽선을 검출할 수 있었다.