• Journal of Convergence for Information Technology
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• v.7 no.3
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• pp.73-81
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• 2017

The generalized Hough transform (GHough) is a useful technique for detecting and locating 2-D model. However, GHough requires a 4-D parameter array and a large amount of time to detect objects of unknown scale and orientation because it enumerates all possible parameter values into a 4-D parameter space. Several n-to-1 mapping algorithms were proposed to reduce the parameter space from 4-D to 2-D. However, these algorithms are very likely to fail due to the random votes cast into the 2-D parameter space. This paper proposes to use internal gradient information in addition to the model boundary points to reduce the number of random votes cast into 2-D parameter space. Experimental result shows that our proposed method can reduce both the number of random votes cast into the parameter space and the execution time effectively.

• Journal of KIISE:Software and Applications
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• v.30 no.10
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• pp.973-982
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• 2003

This paper presents an efficient method for automatically detecting objects in a given image. The GHT is a robust template matching algorithm for automatic object detection in order to find objects of various shapes. Many different templates are applied by the GHT in order to find objects of various shapes and size. Every boundary detected by the GHT scan be used as an initial outline for more precise contour-finding techniques. The main weakness of the GHT is the excessive time and memory requirements. In order to overcome this drawback, the proposed algorithm uses a multiresolution search by scaling down the original image to half-sized and quarter-sized images. Using the information from the first iterative GHT on a quarter-sized image, the range of nuclear sizes is determined to limit the parameter space of the half-sized image. After the second iterative GHT on the half-sized image, nuclei are detected by the fine search and segmented with edge information which helps determine the exact boundary. The experimental results show that this method gives reduction in computation time and memory usage without loss of accuracy.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.93-101
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• 2004

A face boundary can be approximated by an ellipse with five-dimensional parameters. This property allows an ellipse detection algorithm to be adapted to detecting faces. However, the construction of a huge five-dimensional parameter space for a Hough transform is quite unpractical. Accordingly, we Propose a selectively attentional Hough transform method for detecting faces from a symmetric contour in an image. The idea is based on the use of a constant aspect ratio for a face, gradient information, and scan-line-based orientation decomposition, thereby allowing a 5-dimensional problem to be decomposed into a two-dimensional one to compute a center with a specific orientation and an one-dimensional one to estimate a short axis. In addition, a two-point selection constraint using geometric and gradient information is also employed to increase the speed and cope with a cluttered background. After detecting candidate face regions using the proposed Hough transform, a multi-layer perceptron verifier is adopted to reject false positives. The proposed method was found to be relatively fast and promising.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.1022-1024
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• 2020

본 논문에서는 구면 영상을 사용한 vSLAM에 의해 생성된 환경 지도에서 실내 공간을 인식하는 방법을 제안한다. 환경 지도는 오픈 소스 라이브러리 OpenVSLAM을 사용하여 생성했다. 카메라 방향과 위치를 기준으로 랜드 마크를 분류하고 허프 변환을 사용해서 실내 공간의 각 벽의 위치를 찾아냈다. 실험 결과 추정된 평면들이 실제 벽면과 유사한 위치에 나타남을 알 수 있었다. 제시하는 알고리즘은 현재의 AR 콘텐츠보다 진보된 AR 콘텐츠를 제작하는 데 사용할 수 있다.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.135-142
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• 2020

In this paper, we describe the iris localization method in RGB images. Most of the iris localization methods are developed for infrared images, thus an iris localization method in RGB images is required for various applications. The proposed method consists of four stages: i) detection of the candidate irises using circular Hough transform (CHT) from an input image, ii) detection of a pupil center based on deep learning, iii) determine the iris using the pupil center, and iv) correction of the iris region. The candidate irises are detected in the order of the number of intersections of the center point candidates after generating the Hough space, and the iris in the candidates is determined based on the detected pupil center. Also, the error due to distortion of the iris shape is corrected by finding a new boundary point based on the detected iris center. In experiments, the proposed method has an improved accuracy about 27.4% compared to the CHT method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.11a
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• pp.273-275
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• 2011

본 논문에서는 허프변환 및 HSV 색변환을 이용한 효율적인 차선검출의 최적화 알고리즘을 제안한다. 차선 검출의 고속화를 위해 차선과 카메라의 위치를 감안하여 고정된 관심영역(ROI_LB)을 정하고 검출 영역을 감소시킨다. 정해진 관심영역 내에서 허프변환을 적용해 차선을 검출하고 이를 위해 Sobel Mask와 Threshold를 사용한다. 또한, HSV 색 공간을 이용하여 황색 선과 백색 선을 구별해내며 차선 이동 시에 "MOVEMENT"이라는 문자열을, 중앙선을 넘어가면 "DANGEROUS"이라는 문자열을 출력한다. 제안하는 방법의 실험 결과는 복잡한 도로 동영상에서 효과적으로 차선을 인식하고 색 구별을 하였으며 제안 방법의 유효성을 검증하기 위해 다양한 실제 차선 패턴을 대상으로 한 실험결과를 제시한다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.147-154
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• 2004

In this paper, Inverted Coordinates Image Space (ICIS) is proposed as a solution for the problem of the unbounded accumulator space in the automatic detection of the finite/infinite vanishing points in image space. Since the ICIS is based on the direct transformation from the image space, it does not lose any geometrical information from the original image and it does not require camera calibration as opposed to the Gaussian sphere based methods. Moreover, the proposed method can accurately detect both the finite and infinite vanishing points under a small fixed memory amount as opposed to the conventional image space based methods. Experiments are conducted on various real images in architectural environments to show the advantages of the proposed approach over conventional methods.

• Annual Conference on Human and Language Technology
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• 1989.10a
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• pp.168-173
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• 1989

데이터의 압축은 화일의 저장공간과 전송시간을 줄이는 중요한 이점을 제공한다. 국내에는 많은 경우 데이터 화일에 2 바이트로 구성된 표준한글부호를 포함하고 있다. 본 논문에서는 2 바이트로 부호화 된 한글을 포함한 데이터 화일을 허프만 부호화 방식에 의해 압축 할때 한글을 한 바이트 단위로 인식하여 압축하는 경우와 두 바이트 단위로 인식하여 압축하는 경우의 여러가지 압축 특성을 비교하였다. 아울러 사전에 조사된 한글의 찾기 순서에 따라 고정된 압축 부호를 사용하는 경우와 앞에서 제시된 방법들을 비교하였다. 비교 결과 두 바이트 단위로 인식하여 압축하는 방법이 더 좋은 압축율을 보이었다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.443-450
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• 2014

To fulfill the recent increasement in the public and private demands for various spatial data, the central and local governments started to produce those data. The low-level land cover map has been produced since 2000, yet the production of high-level land covered map has started later in 2010, and recently, a few regions was completed recently. Although many studies have been carried to improve the quality of land that covered in the map, most of them have been focused on the low-level and mid-level classifications. For that reason, the study for high-level classification is still insufficient. Therefore, in this study, we suggested the automatic extraction of land readjustment for paddy land that updated in the mid-level land mapping. At the study, the RapidEye satellite images, which consider efficient to apply in the agricultural field, were used, and the high pass filtering emphasized the outline of paddy field. Also, the binary images of the paddy outlines were generated from the Otsu thresholding. The boundary information of paddy field was extracted from the image-to-map registrations and masking of paddy land cover. Lastly, the snapped edges were linked, as well as the linear features of paddy outlines were extracted by the regional Hough line extraction. The start and end points that were close to each other were linked to complete the paddy field outlines. In fact, the boundary of readjusted paddy fields was able to be extracted efficiently. We could conclude in that this study contributed to the automatic production of a high-level land cover map for paddy fields.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.3
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• pp.96-106
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• 2009

Extending the scale of the distributed processing in a single Ethernet cluster is physically restricted by maximum ports per switch. This paper presents an implementation of MPI-based multicluster consisting of multiple Ethernet switches for extending the scale of distributed processing, and a asymptotical analysis for communication overhead through execution-time analysis model. To determine an optimum task partitioning, we analyzed the processing time for various partitioning schemes, and AAP(accumulator array partitioning) scheme was finally chosen to minimize the overall communication overhead. The scope of data partitioned in AAP was modified to fit for incremented nodes, and suitable load balancing algorithm was implemented. We tried to alleviate the communication overhead through exploiting the pipelined broadcast and flat-tree based result gathering, and overlapping of the communication and the computation time. We used the linear pipeline broadcast to reduce the communication overhead in intercluster which is interconnected by a single link. Experimental results shows nearly linear speedup by the proposed parallel distributed GHT implemented on MPI-based Ethernet multicluster with four 100Mbps Ethernet switches and up to 128 nodes of Pentium PC.