• Journal of Convergence for Information Technology
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• v.7 no.6
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• pp.143-151
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• 2017

The generalized Hough transform(GHough) can be used effectively for detecting and extracting an arbitrary-shaped 2-D model in an input image. However, the main drawbacks of the GHough are both heavy computation and an excessive storage requirement. Thus, most of the researches so far have focused on reducing both the time and space requirement of the GHough. But it is still not clear how well their improved algorithms will perform under various noise in an input image. Thus, this paper proposes a new framework that can measure the performance of the GHough quantitatively. For this purpose, we view the GHough as a detector in signal detection theory and the ROC curve will be used to specify the performance of the GHough. Finally, we show that we can evaluate the GHough under various noise conditions in an input image.

• 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.

• 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.

• 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 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.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1984-1987
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• 2003

본 논문에서는 모델에 기반한 2차원 영상인식 알고리즘 중에 하나인 일반화된 허프변환(Generalized Hough Transform)에 대하여 색상정보까지 포함할 수 있도록 기존의 알고리즘을 확장하는 방법을 제시하였고, 이에 의한 실험결과를 간단히 고찰하였다. 기존의 일반화된 허프변환은 대상물의 윤곽선 정보에 기반을 두었기 때문에, 윤곽선 정보가 일치하면 대상물의 색상이나 명암분포가 달라도 동일한 대상물로 인식할 가능성이 있다. 따라서, 일반화된 허프변환을 확장하여 대상물의 모델링과 인식과정에 색상정보(chromatic information)를 포함한다면 2D 영상인식시 컬러정보를 활용할 수 있는 장점이 있다. 여기에서는 실제로 모델링 과정과 인식과정에서 색상정보를 반영하기 위한 간략한 방법과, 이에 따른 실험결과를 제시하였다. 간단한 2D 위치변환이 존재하는 실험에서 윤곽선의 모양이 거의 일치하더라도 색상이 다른 대상물이 존재할 경우에 이를 올바로 구분할 수 있었다.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.8
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• pp.67-75
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• 2000

In this paper, we proposed a new method to find dive parameters of an ellipse from the optical Hough transform (HT) results. The method employs the HT for detection of a straight line and the one-dimensional analysis of the resultant parameter domain. Using this algorithm, we simulated about the ellipses with different positions, and obtained the information of the ellipse with 94% accuracy in the worst case. To compare the simulation results with the experimental ones, we performed optical experiments using a HT Computer Generated Hologram (CGH) filter. Through the experiments, we showed that our results were very similar to the simulation results.

• The Transactions of the Korea Information Processing Society
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• v.7 no.11
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• pp.3566-3575
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• 2000

In this paper, we propose an simple and efficient method to estunate the camera operation by using compressed information, which is extracted diracily from MPEG2 stream without complete decoding. In the method, the motion vector is converted into approximate optical flow by using the feature of predicted frame, because the motion vector in MPEG2 video stream is not regular sequene. And they are used to estimate the camera operation, which consist of pan, and zoom by Hough transform technique. The method provided better results than the least square method for video stream of basketball and socer games. The proposed method can have a reduced computational complexity because the information is directiv abtained in compressed domain. Additionally it can be a useful technology in content-based searching and analysis of video information. Also, the estimatd cameral operationis applicable in searching or tracking objects in MPEG2 video stream without decoding.

• 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 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