• Title/Summary/Keyword: Edge Detection

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A Study on Endpoint Detection and Syllable Segmentation System Using Ramp Edge Detection (Ramp Edge Detection을 이용한 끝점 검출과 음절 분할에 관한 연구)

  • 유일수;홍광석
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.2216-2219
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    • 2003
  • Accurate speech region detection and automatic syllable segmentation is important part of speech recognition system. In automatic speech recognition system, they are needed for the purpose of accurate recognition and less computational complexity, In this paper, we Propose improved syllable segmentation method using ramp edge detection method and residual signal Peak energy. These methods were used to ensure accuracy and robustness for endpoint detection and syllable segmentation system. They have almost invariant response to various background noise levels. As experimental results, we obtained the rate of 90.7% accuracy in syllable segmentation in a condition of accurate endpoint detection environments.

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Spectral Pattern Based Robust Speech Endpoint Detection in Noisy Environments (스펙트럼 패턴 기반의 잡음 환경에 강인한 음성의 끝점 검출 기법)

  • Park, Jin-Soo;Lee, Yoon-Jae;Lee, In-Ho;Ko, Han-Seok
    • Phonetics and Speech Sciences
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    • v.1 no.4
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    • pp.111-117
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    • 2009
  • In this paper, a new speech endpoint detector in noisy environment is proposed. According to the previous research, the energy feature in the speech region is easily distinguished from that in the speech absent region. In conventional method, the endpoint can be found by applying the edge detection filter that finds the abrupt changing point in feature domain. However, since the frame energy feature is unstable in noisy environment, the accurate edge detection is not possible. Therefore, in this paper, the novel feature extraction method based on spectrum envelop pattern is proposed. Then, the edge detection filter is applied to the proposed feature for detection of the endpoint. The experiments are performed in the car noise environment and a substantial improvement was obtained over the conventional method.

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Using mean shift and self adaptive Canny algorithm enhance edge detection effect (Mean Shift 알고리즘과 Canny 알고리즘을 이용한 에지 검출 향상)

  • Lei, Wang;Shin, Seong-Yoon;Rhee, Yang-Won
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2009.01a
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    • pp.207-210
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    • 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.

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An Edge Detection Method for Gray Scale Images Based on their Fuzzy System Representation

  • Moon, Byung-Soo;Lee, Hyun-Chul;Kim, Jang-Yeol
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.12a
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    • pp.283-286
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    • 2001
  • Based on a fuzzy system representation of gray scale images, we derive an edge detection algorithm whose convolution kernel is different from the known kernels such as those of Roberts', Prewitt's or Sobel's gradient. Our fuzzy system representation is an exact representation of the bicubic spline function which represents the gray scale image approximately. Hence the fuzzy system is a continuous function and it provides a natural way to define the gradient and the Laplacian operator. We show that the gradient at grid points can be evaluated by taking the convolution of the image with a 3 3 kernel. We also show that our gradient coupled with the approximate value of the continuous function generates an edge detection method which creates edge images clearer than those by other methods. A few examples of applying our methods are included.

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Vision chip for edge detection with a function of pixel FPN reduction (픽셀의 고정 패턴 잡음을 감소시킨 윤곽 검출용 시각칩)

  • Suh, Sung-Ho;Kim, Jung-Hwan;Kong, Jae-Sung;Shin, Jang-Kyoo
    • Journal of Sensor Science and Technology
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    • v.14 no.3
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    • pp.191-197
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    • 2005
  • When fabricating a vision chip, we should consider the noise problem, such as the fixed pattern noise(FPN) due to the process variation. In this paper, we propose an edge-detection circuit based on biological retina using the offset-free column readout circuit to reduce the FPN occurring in the photo-detector. The offset-free column readout circuit consists of one source follower, one capacitor and five transmission gates. As a result, it is simpler and smaller than a general correlated double sampling(CDS) circuit. A vision chip for edge detection has been designed and fabricated using $0.35\;{\mu}m$ 2-poly 4-metal CMOS technology, and its output characteristics have been investigated.

A $160{\times}120$ Light-Adaptive CMOS Vision Chip for Edge Detection Based on a Retinal Structure Using a Saturating Resistive Network

  • Kong, Jae-Sung;Kim, Sang-Heon;Sung, Dong-Kyu;Shin, Jang-Kyoo
    • ETRI Journal
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    • v.29 no.1
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    • pp.59-69
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    • 2007
  • We designed and fabricated a vision chip for edge detection with a $160{\times}120$ pixel array by using 0.35 ${\mu}m$ standard complementary metal-oxide-semiconductor (CMOS) technology. The designed vision chip is based on a retinal structure with a resistive network to improve the speed of operation. To improve the quality of final edge images, we applied a saturating resistive circuit to the resistive network. The light-adaptation mechanism of the edge detection circuit was quantitatively analyzed using a simple model of the saturating resistive element. To verify improvement, we compared the simulation results of the proposed circuit to the results of previous circuits.

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Noise Estimation Using Edge Detection (에지 검출을 이용한 잡음 예측)

  • Kim, Young-Ro;Dong, Sung-Soo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.5
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    • pp.281-286
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    • 2013
  • In this paper, we propose a noise estimation method using edge detection. It is a filter-based noise estimation method. Edge detection is to exclude structures and details which have an effect on the noise estimation. To detect edge, we use a modified rational filter which is robust to details of images. The proposed noise estimation method is more efficiently applied to noise estimation in various types of images and has better results than those of conventional filter-based noise estimation methods.

Comparison of Various Edge Detection Techniques Using 2D Intensity Image (2D 영상에서의 에지 검출 기법들의 비교 연구)

  • Yang, Woo-Suk;Cho, Nam-Gook
    • Proceedings of the KIEE Conference
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    • 1995.07b
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    • pp.883-885
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    • 1995
  • Edges are one of the most important features used in various computer vision applications. Most of the known edge detection techniques are categorized into three gropus: First two approaches are to find gray level changes using first-order or second-order differentiation. The third method uses intrinsic propoeties of edges such as the result shown during scale space filtering. In this paper, we study various kind of edge detection techniques. Two images (Lenna image and a certain image which is composed of step, ramp, roof, and other artificial edge patterns) are used to compare different edge detection techniques and to verify the advantages and disadvantage of each techniques.

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Image Change Tracking System (영상 변화 추적 시스템)

  • Park Young-Hwan
    • Geophysics and Geophysical Exploration
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    • v.2 no.3
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    • pp.154-158
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    • 1999
  • This paper introduces a partial edge detection technique, that improves the processing time of an automatic change tracking system for multi-temporal images. In the conventional change tracking systems for multi-temporal images, the edge detection is performed over the whole image. In the proposed method, however, the necessary portions for the edge detection is selected first and the edge detection is performed over the selected parts only. As a consequence, the improvement in the processing time could be achieved. The proposed change tracking system is expected to be utilized as a very efficient tool to configure changes in large data set such as remotely sensed satellite imagery or geophysical time laps images.

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Multiresolution Edge Detection Technique (다해상도 에지 검출 기법)

  • 박덕준;박래홍
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.28B no.12
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    • pp.51-58
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    • 1991
  • In this paper, we propose a multiresolution edge detection method which selects the edge detection window size and scale automatically by using the local variance information as an edgeness measure of a region. The mode of the local variance distribution which is calculated over the (2p + 1) x (2p + 1) windows is used to determine the resolution of the given pixel and the edge operator with different scale can be applied to the pixel depending on its resolution. The combination of the resolution determination scheme with the conventional Canny and LOG edge detectors gives the proposed multiresolution edge detection schemes. The effectness of the proposed schemes is shown via computer simulation.

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