• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2006.06a
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• pp.81-84
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• 2006

본 논문에서는 시스템 수준 설계 언어인 SystemC를 이용하여 디지털 이미지 프로세싱의 한 부분인 Edge Detector 구현에 대하여 기술한다. Edge Detector는 마스크의 가운데 픽셀을 강조하는 Sobel 알고리즘을 사용하여 모델링 하였으며, 설계된 디자인의 동작은 간단한 BMP 파일을 적용하여 검증하였다. 또한 Edge Detector를 구성하는 하위 모듈들 간의 연결을 각각 sc_buffer 채널과 so_fifo 채널을 이용하여 설계하였을 때의 실행시간을 비교하였다.

• 한국데이터정보과학회:학술대회논문집
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• 2004.04a
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• pp.197-201
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• 2004

We describe a new edge detector based on the robust rank-order (RRO) test which is a useful alternative to Wilcoxon test, using $r{\times}r$ window for detecting edges of all possible orientations in noisy images. Some experiments of statistical edge detectors based on the Wilcoxon test and T test with our RRO detector are carried out on synthetic and real images corrupted by both Gaussian and impulse noise. We also implement these edge detectors using Java on the Web.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.133-141
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• 2005

An edge is where the intensity of an image moves from a low value to high value or vice versa. The edges tell where objects are. their shape and size. and something about their texture. Many traditional edge operators are derivative based and perform reasonably well for simple noise-free images. In recent, statistical edge detectors for complex images with noises have been described. This paper compares and analysis the performance of statistical edge detectors based on the T test and Wilcoxon test, and mathematical edge detectors based on Sobel operator, and the well-known Canny detector and Wavelet transformation detector, and provides the implementation of these edge detectors using Java on the web.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.241-248
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• 2007

In predictive image coding, a LS (Least Squares)-based adaptive predictor is an efficient method to improve image edge predictions. This paper proposes a hybrid interpolation with weighted edge detector. A hybrid approach of switching between bilinear interpolation and EDI (Edge-Directed Interpolation) is proposed in order to reduce the overall computational complexity The objective and subjective quality is also similar to the bilinear interpolation and EDI. Experimental results demonstrate that this hybrid interpolation method that utilizes a weighted edge detector can achieve reduction in complexity with minimal degradation in the interpolation results.

• The Korean Journal of Applied Statistics
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• v.20 no.1
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• pp.147-157
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• 2007

Edge detection has been widely used in computer vision and image processing. We describe a new edge detector based on the robust rank-order test which is a useful alternative to Wilcoxon test. Our method is based on detecting pixel intensity changes between two neighborhoods with a $r{\times}r$ window using an edge-height model to perform effectively on noisy images. Some experiments of our robust rank-order detector with several existing edge detectors are carried out on both synthetic images and real images with and without noise.

• Journal of information and communication convergence engineering
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• v.8 no.3
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• pp.339-342
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• 2010

An iris image pattern positioning with preserved edge detector, ring zone and clock zone, frequency distribution and overlay matching is presented in this paper. Edge detector is required to be powerful and detail. That is proposed by overlaying Canny with LOG (CLOG). The two reference patterns are made from allocating each gray level on the clock zone and ring zone respectively. The normalized target image is overlaid with the clock zone reference pattern and the ring zone pattern to extract overlapped number, and make a matched frequency distribution to look through a symptom and position of human organ and tissue. The iterating experiments result in the ring and clock zone positioning evaluation.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.464-466
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• 1998

경계선 검출은 시각 인식 또는 기계 시각 인식의 과정에서 제일 먼저 수행되는 전처리 단계이다. 경계선 검출은 컴퓨터 시각 인식성능에 매우 중대한 요인으로 작용한다. 최근 MPEG-4에서 Model Based Coding 기법이 채택되면서, 경계선 검출 및 이를 이용한 컴퓨터 시각 인식의 중요성은 날로 커지고 있다. 한편, 잡음이 있는 영상의 경계선 검출 방법으로 여러 가지가 제시되었는데, 특히 잡음의 종류가 Additive White Gaussian인 경우에는 Canny Edge Detector가, Impulse인 경우에는 Dual Stack Filter를 적용한 방법이 각각 높은 성능으로 인정을 받고 있다. 그러나 Canny Edge Detector의 경우, Canny는 이론적인 Optimal Filter를 구하는 데에 성공하였지만 실제 적용에는, 이 Optimal Filter의 근사로써 Gauss함수의 1계 도함수를 사용하였다. 본 연구에서는 Gauss함수보다는 상당히 Optimal Filter와 가까운 Filter를 얻기 위하여 웨이블릿 변환을 사용한 Liao등의 방법과, 각기 다른 Scale에서의 웨이블릿 변환들이 가지는 잡음과의 관계를 고려한 새로운 경계선 검출방법을 개발하였다. 실험결과, 본 연구에서의 방법은 기존에 사용되던 Canny Edge Detector나 Stochastic Operator보다 뛰어난 성능을 보여주었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1925-1931
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• 2011

This paper suggests an approach to the subtle concept, "good", through the fuzzy logic and the design of the Canny edge detector of Gray scale images based on the rules of fuzzy anisotropic diffusion. The Canny edge detection algorithms design is to divide the gray levels into pixels and then calculate the diffusion coefficients at each pixel of non-edgy regions. Based on this processing, we present the Canny edge detector implementing fuzzy logic and comparing the results to other existing methods. The proposed approach is the narrow dynamic range of the gray-level image Sharpening the edge detection and has the advantage.

• Progress in Medical Physics
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• v.20 no.4
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• pp.191-198
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• 2009

In this study, we evaluated an edge detector for small-beam dosimetry. We measured the dose linearity, dose rate dependence, output factor, beam profiles, and percentage depth dose using an edge detector (Model 1118 Edge) for 6-MV photon beams at different field sizes and depths. The obtained values were compared with those obtained using a standard volume ionization chamber (CC13) and photon diode detector (PFD). The dose linearity results for the three detectors showed good agreement within 1%. The edge detector had the best linearity of ${\pm}0.08%$. The edge detector and PFD showed little dose rate dependency throughout the range of 100~600 MU/min, while CC13 showed a significant discrepancy of approximately -5% at 100 MU/min. The output factors of the three detectors showed good agreement within 1% for the tested field sizes. However, the output factor of CC13 compared to the other two detectors had a maximum difference of 21% for small field sizes (${\sim}4{\times}4\;cm^2$). When analyzing the 20~80% penumbra, the penumbra measured using CC13 was approximately two times wider than that using the edge detector for all field sizes. The width measured using PFD was approximately 30% wider for all field sizes. Compared to the edge detector, the 10~90% penumbras measured using the CC13 and PFD were approximately 55% and 19% wider, respectively. The full width at half maximum (FWHM) of the edge detector was close to the real field size, while the other two detectors measured values that were 8~10% greater for all field sizes. Percentage depth doses measured by the three detectors corresponded to each other for small beams. Based on the results, we consider the edge detector as an appropriate small-beam detector, while CC13 and PFD can lead to some errors when used for small beam fields under $4{\times}4\;cm^2$.

• Journal of information and communication convergence engineering
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• v.12 no.3
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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.