• Title/Summary/Keyword: Generalized Hough Transform

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Edge-Based Matching Using Generalized Hough Transform and Chamfer Matching (Generalized Hough Transform과 Chamfer 정합을 이용한 에지기반 정합)

  • Cho, Tai-Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.1
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    • pp.94-99
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    • 2007
  • In this paper, a 2-dimensional edge-based matching algorithm is proposed that combines the generalized Hough transform (GHT) and the Chamfer matching to complement weakness of either method. First, the GHT is used to find approximate object positions and orientations, and then these positions and orientations are used as starling parameter values to find more accurate position and orientation using the Chamfer matching. Finally, matching accuracy is further refined by using a subpixel algorithm. The algorithm was implemented and successfully tested on a number of images containing various electronic components.

Fiducial Mark Recognition Using Generalized Hough Transform (Generalized Hough Transform을 이용한 Fiducial Mark 인식)

  • 조태훈
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.04b
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    • pp.568-570
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    • 2001
  • fiducial mark는 PCB 정밀조립/검사 장비에서 위치보정을 위해 필수적으로 사용되는데, 실제 생산현장에서의 fiducial mark의 품질은 완전하지 않고, 손상된 상태인 경우가 많이 발생한다. 기존에 주로 사용되는 blob centroid 방법에 의한 mark의 위치추출은 mark의 상태가 손상되었을 경우, 큰 오차를 수반하게 된다. 본 논문에서는 Generalized Hough Transform을 이용한 fiducial mark의 중심위치 기법을 개발하여, 적용한 결과 손상된 mark에 대해서도 매우 강건한 결과를 보여주었다.

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Locating Reinforcing Bars in Concrete Structures Using Generalized Hough Transform of Radar Image (일반화 Hough변환을 응용한 콘크리트 레이더 화상 내 실제 철근위치의 검출 해석)

  • ;魚本健人
    • Journal of the Korea Concrete Institute
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    • v.12 no.1
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    • pp.23-31
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    • 2000
  • Locating reinforcing bars, in particular to know their accurate depths, is very important in radar inspection of concrete structures. By the way, an accurate depth estimation of reinforcing bars in concrete structures by the radar is not easy because the microwave propagation velocity in test area is generally unknown. This problem can be solved by generalized Hough transformation technique. Using this technique, the microwave propagation velocity in test area can be detected from the radar image, which appear as hyperbolas conveying the velocity information in their shape. A developed speed-up technique for the computation of the Generalized Hough transformation is also investigated in this study. As a result, although it becomes difficult to locate reinforcing bars when multiple parallel bars lying too close together, there is a possibility of detecting accurate depths of reinforcing bars in test area by the proposed method

Specialized VLSI System Design for the Generalized Hough Transform (일반화된 Hough 변환을 위한 특수 목적 VLSI 시스템 설계에 관한 연구)

  • 채옥삼;이정헌
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.3
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    • pp.66-76
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    • 1995
  • In this research, a mesh connected VLSI structure is proposed for the real time computation of the generalized Hough transform(GHT). The purpose of the research is to design a generalized Hough transformer that can be realized as a single chip processor. The GHT has been modified to yield a highly parallel structure consisting of simple processing elements(PEs) and communication networks. In the proposed structure, the GHT can be computed by first assigning an image pixel to a PE and performing shift and add operations. The result of the CAD circuit simulation shows that it can be computed in the time proportional to the number of pixels in the pattern. In addition to the Hough transformer, the peak detector has been designed to reduce 1)the number of the I/O operations between the transformer and the host computer and 2) the host computer's burden for peak detection by transmitting only the local peaks detected from the transformed accumulator. It is expected that the proposed single chip Hough transformer with peak detector makes a fast and inexpensive edge based object recognition systems possible for many industrial and military applications.

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The Hough Transform - A Radon-Like Transform

  • Thue Nguyen Dinh;Due Duong Anh
    • Proceedings of the IEEK Conference
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    • summer
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    • pp.274-275
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    • 2004
  • The Hough transform has been used as a tool for line detection. The main idea of the Hough transform is to transform each pixel in the image individually into the parameter domain. In this way, the Hough transform converts a difficult global detection problem in the image domain into a more easily solved local peak detection problem in the parameter domain. In this paper, we show that the discrete Hough transform is identical to the discrete Radon transform. Thus, we can use the generalized Radon transform to handle more general parameterized curve types.

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A Selection of Threshold for the Generalized Hough Transform: A Probabilistic Approach (일반화된 허프변환의 임계값 선택을 위한 확률적 접근방식)

  • Chang, Ji Y.
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.1
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    • pp.161-171
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    • 2014
  • When the Hough transform is applied to identify an instance of a given model, the output is typically a histogram of votes cast by a set of image features into a parameter space. The next step is to threshold the histogram of counts to hypothesize a given match. The question is "What is a reasonable choice of the threshold?" In a standard implementation of the Hough transform, the threshold is selected heuristically, e.g., some fraction of the highest cell count. Setting the threshold too low can give rise to a false alarm of a given shape(Type I error). On the other hand, setting the threshold too high can result in mis-detection of a given shape(Type II error). In this paper, we derive two conditional probability functions of cell counts in the accumulator array of the generalized Hough transform(GHough), that can be used to select a scientific threshold at the peak detection stage of the Ghough.

Optical implementation of the Hough transform for both line and circle parameterization by use of rotationally multiplexed holograms (회전다중 홀로그램을 이용한 선 및 원 파라미터화를 위한 Hough 변환의 광학적 구현)

  • 신동학;장주석
    • Korean Journal of Optics and Photonics
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    • v.9 no.5
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    • pp.321-325
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    • 1998
  • We explain that a holographic filter of the generalized Hough transform can be easily obtained by use of rotational multiplexing in hologram recording. To show the feasibility of our approach experimentally, we recorded the Hough transform filter of both line and circle parameterization by combined use of rotational and angle multiplexing. Experimental results on the Hough transform for a few input patterns are presented.

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Automatic Detection of Left Ventricular Contour from 2-D Echocardiograms using Fuzzy Hough Transform (퍼지 Hough 변환에 의한 2-D 심초음파도에서의 좌심실 윤곽 자동검출)

  • ;K.P
    • Journal of Biomedical Engineering Research
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    • v.13 no.2
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    • pp.115-124
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    • 1992
  • An algorithm has been proposed for the automatic detection of optimal epiand endocardial left ventricular borders from 2-D short axis echocardiogram which is degraded by noise and echo drop out. For the implementation of the algorithm, we modified Ballard's Generalized Hough Transform which can be applicable only for deterministic object border, and newly proposed Fuzzy Hough Transform method. The algorithm presented here allows detection of object whose exact shapes are unknown. The algorithm only requires an approximate model of target object based on anatomical data. To detect the approximate epicardial contour of left ventricle, Fuzzy Hough Transform was applied to the echocardiogram. The optimal epicardial contour was founded by using graph searching method which contains cost function analysis process. Using this optimal epicardial contour and average thickness imformation of left ventricular wall, the approximate endocardial line was founded, and graph searching method was also used to detect optimal endocardial contour.

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A study on the modified hough transform for hangul feature extraction using generalized sampling rule (한글 특징점 추출을 위한 일반화된 표본화 알고리즘을 이용한 수정된 Hough Transform에 관한 연구)

  • 구하성;고형화
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.9
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    • pp.142-149
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    • 1994
  • Hangul is expressed by the basic elements, twenty-four characters. Because these characters are composed of a circle and lines, Hough transform(HT), which has a powerful performance on the noise in extracting lines, is introduced. Many difficulties often occur when the original HT is used to extract strokes and it's direction, position and length from handwritten Hangul characters. Original HT has eight direction selected as samples in the transformed image should be calculated for these eight directions. In this paper, the generalized sampling rule is suggested. According to the rule, those directions which are possible to a line are the only thing to be calculated. The experoment result turned out to be higher than the method that Chen suggested in sampling rate. Anogher experiment result is done on the 1800 handwritten Hangul characters that 10 persons wrote. By feature extracting the oritinal HT and sampling HT. And as a result of six type classification, the suggested method came out higher than original HT.

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A Study on the Classification of Hand-written Korean Character Types using Hough Transform (Hough Transform을 이용한 한글 필기체 형식 분류에 관한 연구)

  • 구하성;고경화
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.19 no.10
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    • pp.1991-2000
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    • 1994
  • In this paper, an alagorithm with six types of classification is suggested for the recognition system of hand-written Korean characters. After thinning process and truncating process for noise redection. The input images are used generalized by $64\times64$ size. The six type classification is composed of preliminary and secondary classification process by using the learning algoritm of multi-layer perceptron. Subblock Hough transform is used as local feature and sampling Hough transform is used as global feature. Experiment is conducted for 1800 characters which is written 31 times per each type by 10 persons. The 90% recognition rate is resulted by the preliminary classification of detection the final consonant and by the secondary classification of detecting the vowels.

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